The Swiss Election Study (Selects) 2023 consists of four complementary components: The Post-Election Survey (PES), the Panel Survey, the Candidate Survey, and the Media Analysis. The study design is largely inspired by Selects 2019. The PES and Candidate Survey are mixed-mode surveys (online/paper), with a push-to-web design, whereas the Panel Study is an online survey. In April 2022, a call for questions/modules was opened to allow researchers from Switzerland and abroad to include novel questions into one or different components of Selects. Ten out of 14 submitted proposals were selected by the Selects Commission after a review process conducted by internationally renowned election researchers, and were fully or partially integrated into one or several components of Selects 2023. The Selects surveys were approved by the Ethics commission of the University of Lausanne.

Post-Election Survey (PES): The Post-Election Survey consists of 5033 respondents who answered the questionnaire in the period from 23 October 2023 to 12 January 2024. The survey was conducted in a sequential mixed mode with web offered as the first option: 90% responded in this way, while 10% responded by returning the paper questionnaire that was sent out with the second reminder to those that had not completed the web questionnaire. The sampling was based on a representative sample of around 2’600 Swiss citizens, with an oversampling of small cantons to have at least 50 respondents in every canton. An additional oversampling was done in the cantons of Geneva and Ticino thanks to additional funding from these cantons. The sample was drawn by the Federal Statistics Office from the SRPH. Sample members received an unconditional incentive (10 CHF in cash) that was sent out with the invitation letter. Module 6 Questionnaire of the Comparative Study of Electoral Systems was included into the PES.

Panel Survey: The Panel Survey studies the evolution of opinion and vote intention/choice during the different phases of the election cycle. In 2023, three waves were conducted: the first before the main campaign period (June/early August), the second during the election campaign (September/October), and the third after the elections (October/November). The initial random sample (stratified by big region/NUTS II) was taken by the Federal Statistics Office from the SRPH. 8197 individuals responded to the first wave, 6077 to the second wave, and 5579 to the third wave. Conditional incentives were used in all three panel waves (lottery of 5x300 CHF in wave 1, 10 CHF in cash in waves 2 and 3). The Panel Survey will continue with annual follow-up waves until the 2027 elections. Wave 4 took place between 23 September and 4 November 2024, with 4'919 respondents.

Candidate Survey: The Candidate Survey was carried out among all candidates for the National Council and the Council of States in the framework of the international Comparative Candidate Survey (CCS) project, based on the Round III questionnaire. The survey collects data on the biography, campaign activities, and policy position of the candidates. Among others, the information gathered makes possible the study of underlying factors of candidates’ electoral success, as well as of issues of representation and linkage between voters and elites. In 2023, 2527 out of 5997 candidates participated in the Candidate Survey. This survey was conducted by FORS in collaboration with Politools and the University of Bern.

Media Analysis: On behalf of Selects, the Center for Research & Methods at the University of Applied Sciences in Business Administration Zurich (HWZ) conducted a Media Analysis. The Media Analysis is a supplement to the Panel Survey and makes it possible to analyse the election campaign in the media and its influence on voters' opinion formation. A media study has been part of Selects since 2003. In 2023, 116 daily or weekly newspapers (print and online) were content-analyzed in the period between 1 May 2023 and 31 October 2023.

Geographic coverage

National, regional

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2020 Vietnam COVID-19 High Frequency Phone Survey of Households (VHFPS) uses a nationally representative household survey from 2018 as the sampling frame. The 2018 baseline survey includes 46,980 households from 3132 communes (about 25% of total communes in Vietnam). In each commune, one EA is randomly selected and then 15 households are randomly selected in each EA for interview. We use the large module of to select the households for official interview of the VHFPS survey and the small module households as reserve for replacement. After data processing, the final sample size for Round 2 is 3,935 households.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire for Round 2 consisted of the following sections

Section 2. Behavior Section 3. Health Section 5. Employment (main respondent) Section 6. Coping Section 7. Safety Nets Section 8. FIES

Cleaning operations

Data cleaning began during the data collection process. Inputs for the cleaning process include available interviewers’ note following each question item, interviewers’ note at the end of the tablet form as well as supervisors’ note during monitoring. The data cleaning process was conducted in following steps: • Append households interviewed in ethnic minority languages with the main dataset interviewed in Vietnamese. • Remove unnecessary variables which were automatically calculated by SurveyCTO • Remove household duplicates in the dataset where the same form is submitted more than once. • Remove observations of households which were not supposed to be interviewed following the identified replacement procedure. • Format variables as their object type (string, integer, decimal, etc.) • Read through interviewers’ note and make adjustment accordingly. During interviews, whenever interviewers find it difficult to choose a correct code, they are recommended to choose the most appropriate one and write down respondents’ answer in detail so that the survey management team will justify and make a decision which code is best suitable for such answer. • Correct data based on supervisors’ note where enumerators entered wrong code. • Recode answer option “Other, please specify”. This option is usually followed by a blank line allowing enumerators to type or write texts to specify the answer. The data cleaning team checked thoroughly this type of answers to decide whether each answer needed recoding into one of the available categories or just keep the answer originally recorded. In some cases, that answer could be assigned a completely new code if it appeared many times in the survey dataset.
• Examine data accuracy of outlier values, defined as values that lie outside both 5th and 95th percentiles, by listening to interview recordings. • Final check on matching main dataset with different sections, where information is asked on individual level, are kept in separate data files and in long form. • Label variables using the full question text. • Label variable values where necessary.

Abstract

The Nigerian General Household Survey (GHS) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program and was revised in 2010 to include a panel component (GHS-Panel). The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, inter-institutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of 5,000 households, which are also representative of the geopolitical zones (at both the urban and rural level). The households included in the GHS-Panel are a sub-sample of the overall GHS sample households (22,000). This survey is the third wave of the GHS-Panel, and was implemented in 2015-2016.

Geographic coverage

National Coverage Sector

Analysis unit

Households

Universe

Household Members

Kind of data

Sample survey data [ssd]

Sampling procedure

The GHS-Panel sample is fully integrated with the 2010 GHS Sample. The GHS sample is comprised of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs) chosen from each of the 37 states in Nigeria. This results in a total of 2,220 EAs nationally. Each EA contributes 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,000 households, 5,000 households from 500 EAs were selected for the panel component and 4,916 households completed their interviews in the first wave. Given the panel nature of the survey, some households had moved from their location and were not able to be located by the time of the Wave 3 visit, resulting in a slightly smaller sample of 4,581 households for Wave 3.

In order to collect detailed and accurate information on agricultural activities, GHS-Panel households are visited twice: first after the planting season (post-planting) between August and October and second after the harvest season (post-harvest) between February and April. All households are visited twice regardless of whether they participated in agricultural activities. Some important factors such as labour, food consumption, and expenditures are collected during both visits. Unless otherwise specified, the majority of the report will focus on the most recent information, collected during the post-harvest visit.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The data cleaning process was done in a number of stages. The first step was to ensure proper quality control during the fieldwork. This was achieved in part by using the concurrent data entry system which was designed to highlight many of the errors that occurred during the fieldwork. Errors that are caught at the fieldwork stage are corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then sent from the state to the head office of NBS where a second stage of data cleaning was undertaken. During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information for required variables, sections, questionnaires and EAs. Any problems found were then reported back to the state where the correction was then made. This was an ongoing process until all data were delivered to the head office.

After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete set of data. Where problems were identified, this was reported to the state. There the questionnaires were checked and where necessary the relevant households were revisited and a report sent back to the head office with the corrections.

The final stage of the cleaning process was to ensure that the household- and individual-level datasets were correctly merged across all sections of the household questionnaire. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. This was also done for crop-by-plot information as well.

Abstract

This survey reflects the data for the year 2009, and provides us with the main data about Hotel Guests' expenditure which is related to overnight-stay tourists Objectives of the Survey The survey provided data on The characteristics of hotel guests The characteristics of the visit The length of stay of the visit The amount and mode of expenditure during the visit

Geographic coverage

West Bank

Analysis unit

Hotel Guests

Universe

Hotel Guests

Kind of data

Sample survey data [ssd]

Sampling procedure

Strata of design The sample was distributed to two strata, that is Actual strata the sample was distributed by visitor's nationality strata (resident, non resident Post strata the sample was distributed by visitor's sex, and nationality

Sample size The sample size was estimated to be about 2,214 visitors or guests distributed among West Bank hotels

Design a sample survey The sample was a stratified random sample of a standard one stage A randomly stratified sample was selected of guests from the hotel which was visited A different sample of guests at each hotel was selected depending on the size of the hotel (the number of guests in the hotel data for 2008

Distribution of the sample The distribution sample of the guests in hotels in proportion to the size of each stratum of guests nationality resident, and non resident Publishing levels First level West Bank. and according to the guest nationality 3 nationalitiesSecond level North, Central, South of West Bank, and Jerusalem

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was the main tool for gathering information, so it must conform to the technical specifications of the field work phase, and should meet the requirements of data processing and analysis The questionnaire was designed after considering the methodologies and the recommendations of the United Nations on tourism statistics and taking into account the specificities of the Palestinian community in this aspect

Cleaning operations

The data processing stage consisted of the following steps editing and coding before data entry All questionnaires were edited and coded in the office using the same instructions adopted for editing in the field

Data entry At this stage data was entered into the computer using a data entry template designed in Access. The data entry program was created to satisfy a number of requirements such as Duplication of the questionnaires on the computer screen Check on the logic and consistency of data entered Possibility for internal editing of replies to questions Maintaining a minimum of digital data entry and fieldwork errors User friendly handling Possibility of transferring data into another format to be used and analyzed using other statistical analysis systems such as SPSS

Response rate

97.4%

All hotels in the West Bank were visited and 66 hotels were responded out of 84 The number of questionnaires completed from the guests of the responded hotels was 2157There were 18 hotels from which no completed questionnaires, some of the hotels were not operating during the reference period, some hotels refused to cooperate with fieldworkers, and other hotels the concept of hotel guests does not apply on them because the guests who stay for long-term (more than a year)

Sampling error estimates

Statistical errors These are errors resulting from a study (sample) of the society and not all units of society This survey was implemented on the basis of the sample and therefore data errors could affect the survey results due to the use of a statistical sample rather than a comprehensive inventory of units in the community study and certainly the emergence of differences The values that we expect to be real are obtained through censuses. Calculations can have differences in the related variables

Non-statistical errors The data collection process is characterized by privacy as a result of the nature of the subject, so that the questioning process is subject to greater potential for errors This is because the answers to many questions are subjective and depends on the assessment of the person and is therefore affected by the researcher's degree of awareness during the questioning and other circumstances

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

BRIEF FACE-TO-FACE

The metropolitan, urban and rural population and all .administrative regional units. as defined in Official Europe Union Statistics (NUTS 2) covered proportionately the respective population aged 18 and above. The country was divided into an appropriate number of areas, grouping NUTS regions at whatever level appropriately.

The NUTS covered in the Netherlands were the following; Drente, Flevoland, Friesland, Gelderland, Gröningen, Limburg, Noord-Brabant, Noord-Holland, Overijssel, Utrecht, Zeeland, Zuid-Holland.

The basic sample design was a multi-stage, random probability sample. 100 sampling points were drawn with probability proportional to population size, for a total coverage of the country. The sampling points were drawn after stratification by NUTS 2 region and by degree of urbanisation. They represented the whole territory of the country surveyed and are selected proportionally to the distribution of the population in terms of metropolitan, urban and rural areas. In each of the selected sampling points, one address was drawn at random. This starting address forms the first address of a cluster of a maximum of 20 addresses. The remainder of the cluster was selected as every Nth address by standard random route procedure from the initial address. In theory, there is no maximum number of addresses issued per country. Procedures for random household selection and random respondent selection are independent of the interviewer.s decision and controlled by the institute responsible. They should be as identical as possible from to country, full functional equivalence being a must.

At every address up to 4 recalls were made to attempt to achieve an interview with the selected respondent. There was only one interview per household. The final sample size is 1,085 completed interviews.

POSTAL

The Municipal Population Registry (GBA) was used to select a representative sample of 3,000 individuals, aged 18 and over, of the Dutch population. Municipals were selected first and then the individual sample was drawn up.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

Abstract

Within the frame of PCBS' efforts in providing official Palestinian statistics in the different life aspects of Palestinian society and because the wide spread of Computer, Internet and Mobile Phone among the Palestinian people, and the important role they may play in spreading knowledge and culture and contribution in formulating the public opinion, PCBS conducted the Household Survey on Information and Communications Technology, 2014.

The main objective of this survey is to provide statistical data on Information and Communication Technology in the Palestine in addition to providing data on the following: -

· Prevalence of computers and access to the Internet. · Study the penetration and purpose of Technology use.

Geographic coverage

Palestine (West Bank and Gaza Strip) , type of locality (Urban, Rural, Refugee Camps) and governorate

Analysis unit

Household. Person 10 years and over .

Universe

All Palestinian households and individuals whose usual place of residence in Palestine with focus on persons aged 10 years and over in year 2014.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame The sampling frame consists of a list of enumeration areas adopted in the Population, Housing and Establishments Census of 2007. Each enumeration area has an average size of about 124 households. These were used in the first phase as Preliminary Sampling Units in the process of selecting the survey sample.

Sample Size The total sample size of the survey was 7,268 households, of which 6,000 responded.

Sample Design The sample is a stratified clustered systematic random sample. The design comprised three phases:

Phase I: Random sample of 240 enumeration areas. Phase II: Selection of 25 households from each enumeration area selected in phase one using systematic random selection. Phase III: Selection of an individual (10 years or more) in the field from the selected households; KISH TABLES were used to ensure indiscriminate selection.

Sample Strata Distribution of the sample was stratified by: 1- Governorate (16 governorates, J1). 2- Type of locality (urban, rural and camps).

Sampling deviation

-

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire consists of identification data, quality controls and three main sections: Section I: Data on household members that include identification fields, the characteristics of household members (demographic and social) such as the relationship of individuals to the head of household, sex, date of birth and age.

Section II: Household data include information regarding computer processing, access to the Internet, and possession of various media and computer equipment. This section includes information on topics related to the use of computer and Internet, as well as supervision by households of their children (5-17 years old) while using the computer and Internet, and protective measures taken by the household in the home.

Section III: Data on persons (aged 10 years and over) about computer use, access to the Internet and possession of a mobile phone.

Cleaning operations

Preparation of Data Entry Program: This stage included preparation of the data entry programs using an ACCESS package and defining data entry control rules to avoid errors, plus validation inquiries to examine the data after it had been captured electronically.

Data Entry: The data entry process started on 8 May 2014 and ended on 23 June 2014. The data entry took place at the main PCBS office and in field offices using 28 data clerks.

Editing and Cleaning procedures: Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

Response rate

Response Rates= 79%

Sampling error estimates

There are many aspects of the concept of data quality; this includes the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are three components to the quality of statistics: accuracy, comparability, and quality control procedures.

Checks on data accuracy cover many aspects of the survey and include statistical errors due to the use of a sample, non-statistical errors resulting from field workers or survey tools, and response rates and their effect on estimations. This section includes:

Statistical Errors Data of this survey may be affected by statistical errors due to the use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators.

Variance calculations revealed that there is no problem in disseminating results nationally or regionally (the West Bank, Gaza Strip), but some indicators show high variance by governorate, as noted in the tables of the main report.

Non-Statistical Errors Non-statistical errors are possible at all stages of the project, during data collection or processing. These are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous efforts were made to train the field workers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, and practical and theoretical training took place during the training course. Training manuals were provided for each section of the questionnaire, along with practical exercises in class and instructions on how to approach respondents to reduce refused cases. Data entry staff were trained on the data entry program, which was tested before starting the data entry process.

Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

The sources of non-statistical errors can be summarized as: 1. Some of the households were not at home and could not be interviewed, and some households refused to be interviewed. 2. In unique cases, errors occurred due to the way the questions were asked by interviewers and respondents misunderstood some of the questions.

The 2017/2018 Regional Travel Survey (RTS) collected demographic and travel information from a randomly selected representative sample of households in the National Capital Region Transportation Planning Board (TPB) jurisdictions and adjacent areas, which comprise the TPB model region. It is the primary source of observed data to estimate, calibrate, and validate the regional travel demand model. The model in turn is used for the travel forecasting and air quality conformity analysis of the region’s long-range transportation plan as well as to support other key program activities. The survey data is also used for analyzing regional travel trends and provides a comprehensive picture of travel patterns in the region. The RTS captured information on household, person, and vehicle characteristics in the recruitment survey, and actual observed trip information in a one-day travel diary, which household members recorded details of every trip taken on their assigned travel day.From October 2017 through December 2018, the Regional Travel Survey (RTS) collected information on demographic and travel behavior characteristics of persons living in households in the metropolitan Washington region and adjoining jurisdictions. Under the oversight of COG/TPB, the survey was conducted by a nationally recognized transportation survey research firm, Resource Systems Group, Inc. (RSG). Previous COG/TPB regional household surveys for the Washington area were conducted in 1968, 1987/1988, 1994, and 2007/2008. This document describes the technical approach used for the RTS. It provides a brief overview of the survey methodology. Additional information about the survey methodology, including the questionnaire design, survey sampling, survey administration, targeted outreach, and survey response can be found in the final report prepared by RSG (Appendix A). Due to the complexity of multi-modal travel patterns in the National Capital Region, review and editing of the RTS data files was performed internally by staff familiar with travel patterns in the region. This report is primarily focused on the post-survey data processing and survey expansion performed by COG/TPB staff. Appendices also contain file format and file frequency tables for the final public release files.For more information about the RTS, please visit the RTS webpage.To download the RTS Tabulations, please visit the Regional Travel Survey (RTS) Tabulations page.The RTS Public File is also available by request.

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

A multistage sampling procedure was used to sample the nationally representative households. Thailand is divided into 76 provinces, which are divided into approximately 700 districts.

The district was the first stage unit of selection in the rural areas. The second stage of selection was the villages and the third stage was the household.

The first and second stages of selection for rural areas and the first stage of the urban areas were based on the probability of selection being proportional to the population size (PPS) of the area.

Individuals were randomly selected from the list of eligible voters for each sampled unit. The department of Local Administration, Ministry of Interior, compiles this list which contains names and addresses of eligible voters that are 18 years and older.

The sample included 500 households in Bangkok, 1,000 provincial urban households, and 3,500 rural households.

Mode of data collection

Mail Questionnaire [mail]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

Abstract

The survey provides basic data needed for the development of national policies. The main objectives of the Time Use Survey were as follows:

1. Measurement and analysis of quality of life or general well-being.
2. Identifying demographic and socio-economic characteristics of individuals in Palestinian society.
3. Measurement and valuation of unpaid work (domestic and volunteer work) and development of household production accounts.
4. Improving estimates of paid and unpaid work.
5. Assisting planners and policy makers to develop strategies and policies that may contribute to developmental planning issues.

It is also a rich source of information about the use of time to learn about the nature and structure of individuals in Palestinian society during the year 2012/2013, in different age groups, including children, women, youth and the elderly, and to illuminate the path for decision makers and policy makers in the process of comprehensive national development in this country.

Time Use Survey is a basic tool to determine gender issues. The data enable analysis of the quality of life and an assessment of the extent of female participation in paid and unpaid work (housework and volunteer work) and women's contribution to national accounts.

Geographic coverage

1- Governorate (16 governorates in west bank and Gaza strip) 2- Locality type (urban, rural, camps)

Analysis unit

Individual

Universe

The Target population of the survey consists of all Palestinian individuals of age group 10 years and over, who are living normally with their households in Palestine in 2012/2013 .

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Design After determining the sample size, the sample type is three-stage stratified cluster sample as following:

1- First stage: selecting systematic sample of 220 clusters (enumeration areas). 2- Second stage: selection sample of 21 responded households from each EA selected in the first stage (we use the area sampling to get this number of responded households). 3- Third stage: selection two individuals male and female (10 years and more) from each household selected in second stage using random kish tables.

The population was divided to strata by:

Governorate (16 governorates in west bank and Gaza strip) Locality type (urban, rural, camps)

Sampling deviation

The sample size of the survey is 5,903 Palestinian households.

After determining the sample size, the sample type is three-stage stratified cluster sample as following:

1- First stage: selecting systematic sample of 220 clusters (enumeration areas). 2- Second stage: selection sample of 21 responded households from each EA selected in the first stage (we use the area sampling to get this number of responded households). Third stage: selection two individuals male and female (10 years and more) from each household selected in second stage using random kish tables

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaire The survey questionnaire is the main tool for data collection and was designed on the basis of international surveys specially designed for time use surveys, as well as on the basis of the recommendations of the workshop on time use surveys held in Jordan in 2010. This was organized by ESCWA in cooperation with UNSD to develop a questionnaire for a time use survey and coding manual, along with adding activities related to the Palestinian context compatible with the coding manual of the United Nations of 2006. The questionnaire meets the technical specifications for the field work phase and data processing and analysis requirements. The questionnaire included several sections:

1. Identification Data This identifies a unified means of determining data that define a household, including the divisions of sample design: the number in the enumeration area, governorate and locality, building identification number, number of household, and the name of head of household.

2. Quality Control This is the development of controls of field and office operations and the sequencing in questionnaire stages, usually beginning with data collection through to field and office auditing, data coding, data entry, checks after data entry, and ending with the storage process.

3. Household Members Background Details These include household members, relationship to the head of household, gender, date of birth and age, in addition to other demographic and economic data for the household as a whole.

4. Household Questionnaire This includes questions related to the household in terms of type of housing unit, material used as flooring in the housing unit, primary fuel type used in cooking, goods and services available, monthly household income, and other indicators.

5. Daily Record Questionnaire This part of the questionnaire comprised two time records: in the first record, one male member of the household aged 10 years and above is selected at random and in the second record, one female household member aged 10 years and above is selected at random. The day was divided into periods of time of up to 30 minutes each from midnight until six am and 10 minutes for each period during the day from six am until twelve o'clock at night. The record also contains information that shows whether the activity was performed for a fee or financial return or not. Any secondary activity is also recorded. This information identifies the respondent performing these activities, with whom and the means of transportation or venue where the individual performed the various activities throughout the day (during a 24-hour period).

Cleaning operations

Data verification: comprehensive automated rules of data verification in between questions ensured consistency and identification of answers that were out of range or irrational. This was carried out by a special program performed on a regular basis. The team reviewed error messages and modification of errors based on observations or returned the questionnaire to the field for double checking. The auditing mechanism was prepared by the project management and applied to the data entry program by a programmer where necessary. Appropriate data auditing tests proposed by the project management during the auditing procedure were inclusive and covered all questions in the questionnaire. The questionnaires were drawn from extracted lists and checked automatically, corrected and adjusted on the computer. Then a second list was extracted for the same questionnaires to ensure that the amendment was valid and that all questionnaires had been modified.

Response rate

The sample size of the survey was 5,903 households and 4,605 households were completed. Weights were adjusted to compensate for the non-response cases. The response rate in the survey in Palestine was 79.6% for households

Sampling error estimates

Survey data may be affected by statistical errors as a result of the use of a sample rather than a comprehensive survey covering all units of the study population. Thus, differences may be anticipated from the real values that emerge from a census and variations were calculated for the most important indicators.

The results indicated that there was no problem in the dissemination of data applicable to Palestine as a whole or on a regional basis (the West Bank and the Gaza Strip).

Data appraisal

The concept of data quality includes multiple aspects, starting from initial planning for the survey and ending with data dissemination and interpretation of data for optimal use. The most important components of statistical quality include accuracy, comparability, and quality control procedures. Statistical quality also includes checking and auditing data accuracy in multiple aspects of the survey, particularly statistical errors due to the use of a sample, plus non-statistical errors by staff and the use of survey tools. Response rates may also have a crucial impact on estimates

The Australian Maritime Jurisdiction of approximately 7,000,000 km2 has, at most, 25% of its seabed surveyed at high resolution. Since September 2001, under Commonwealth Policy on Spatial Data Access and Pricing, Intergovernmental Committee on Spatial Data Access and Pricing, the co-custodian of the bathymetry data collected within the Australian Marine Jurisdiction has been assigned to Geoscience Australia (GA). GA thus hosts various formats of raw as well as processed bathymetry datasets from multiple sensors, including multibeam sonar systems. The quality between datasets varies, depending on the objectives of the survey. As of January 2013, the multibeam sonar bathymetric coverage held by GA was acquired by 48 vessels, 26 different multibeam sonar systems in 9 different frequencies between 12 and 455 kHz. Consequently, GA has to deal with a variety of survey standards, making the post-processing and merging not efficient. The objective of this document is thus to provide standards and guidance to GA personnel and contractors who conduct multibeam data acquisition and processing during marine surveys to maximise consistency and efficiency. This document provides the most critical steps to multibeam acquisition and a mandatory checklist and deliverables. Specific details and tips for processing using Caris HIPS & SIPS software and Kongsberg EM series data are also provided in the appendix.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The FAO conducted round 3 of the DIEM-Monitoring household survey between 8 August and 7 September 2022 to monitor changes in agricultural livelihoods and food security in Chad. Data was collected in face-to-face surveys in the provinces of Kanem, Lac, Moyen-Chari and Wadi Fira. A total of 14 departments were targeted and 3704 households interviewed. The data collection for round 3 took place during the rainy (lean) season, whereas the previous survey took place in December 2021, after the harvest. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Data was collected in face-to-face surveys in the provinces of Kanem, Lac, Moyen-Chari and Wadi Fira. A total of 14 departments were targeted and 3704 households interviewed. The data collection for round 3 took place during the rainy (lean) season, whereas the previous survey took place in December 2021, after the harvest.

Mode of data collection

Face-to-face [f2f]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

Abstract copyright UK Data Service and data collection copyright owner.

The National Survey of Bereaved People (VOICES - Views of Informal Carers - Evaluation of Services) is an annual survey designed to measure the quality of end of life care. The VOICES survey particularly focuses on the last three months of life. Results are used to inform policy decisions and enable evaluation of the quality of end of life care by age group, sex, in different settings (home, hospital, care homes and hospices) and by different causes of death. Quality of end of life care is also included as an indicator in the NHS Outcomes Framework and the VOICES survey is used to monitor progress against this.

The Department of Health (DH) first commissioned the survey in 2011 to follow up on a commitment made in the End of Life Care Strategy. Previously, very little systematic information was available about the quality of care delivered to people approaching the end of life, despite reports from the Healthcare Commission and the Neuberger review highlighting deficiencies in care. The commissioning responsibility for the survey moved from DH to NHS England following the restructuring of the Health and Care systems in England in April 2013.

Each year a sample of approximately 49,000 adults who died in England is selected from the deaths registration database held by the Office for National Statistics (ONS). To ensure the sample represents the deaths in England for the given period and covers the key domains of interest, the sample is stratified according to the cause of death, place of death and geography. For the 2011 and 2012 surveys, geography was based on Primary Care Trust (PCT) clusters. For the 2013 survey onwards, this is based on NHS Area Teams (NHS Area Team 2013 has also been applied to the earlier datasets).

The VOICES questionnaire is sent by post to the person who registered the death of the deceased; this is usually a relative or friend of the deceased. Questionnaires are sent out between 4 and 11 months after the patient has died. As is standard in most postal surveys, if no response is received, this first questionnaire is then followed up with two reminders. Once fieldwork, data capture, cleaning and processing are complete, findings are disseminated at both the national and sub-national level.

Further information about the survey and links to related publications may be found on the ONS National Bereavement Survey (VOICES) QMI webpage.

End User Licence and Secure Access versions available
The UK Data Service holds standard End User Licence (EUL) and Secure Access versions of the National Survey of Bereaved People data. EUL data are available to registered users but Secure Access data are only available to ONS Accredited Researchers (in addition, project approval and successful completion of a stringent training course are required before access can be granted). The Secure Access version contains finer detail variables (e.g. IMD deciles as opposed to quintiles in the EUL data, Strategic Clinical Network in addition to NHS Area Teams, and more detailed information on age, causes, dates and place of death). Users are strongly advised to check whether the EUL data are sufficient for their research needs before making an application for the Secure Access version.


Main Topics:
Date, cause and place of death; quality and standards of medical, nursing, social and pastoral care in the last three months of life; support for relatives/carers; demographics of deceased person and respondent.

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Austrian Microcensus is the main household sample survey of Statistics Austria.

The gross sample size is 31,500 dwellings and the net sample size of about 23,000 households. It includes nine samples for the Austrian Länder, ranging between 2,700 and 4,600 dwellings (gross sample size).

In all Länder, except for the city of Vienna and Vorarlberg where the sample is a one-stage stratified-random sample, there is a two-stage-stratified-random sample.

Addresses were drawn from the housing census from 1991 and from the yearly register of newly built dwellings.

Mode of data collection

Mail Questionnaire [mail]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

Hurricane Sandy, the largest storm of historical record in the Atlantic basin, severely impacted southern Long Island, New York in October 2012. In 2014, the U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers (USACE), conducted a high-resolution multibeam echosounder survey with Alpine Ocean Seismic Survey, Inc., offshore of Fire Island and western Long Island, New York to document the post-storm conditions of the inner continental shelf. The objectives of the survey were to determine the impact of Hurricane Sandy on the inner continental shelf morphology and modern sediment distribution, and provide additional geospatial data for sediment transport studies and coastal change model development. For more information about the WHCMSC Field Activity, see https://cmgds.marine.usgs.gov/fan_info.php?fan=2014-072-FA.

These data include the individual responses for the City of Tempe Annual Community Survey conducted by ETC Institute. This dataset has two layers and includes both the weighted data and unweighted data. Weighting data is a statistical method in which datasets are adjusted through calculations in order to more accurately represent the population being studied. The weighted data are used in the final published PDF report.These data help determine priorities for the community as part of the City's on-going strategic planning process. Averaged Community Survey results are used as indicators for several city performance measures. The summary data for each performance measure is provided as an open dataset for that measure (separate from this dataset). The performance measures with indicators from the survey include the following (as of 2023):1. Safe and Secure Communities1.04 Fire Services Satisfaction1.06 Crime Reporting1.07 Police Services Satisfaction1.09 Victim of Crime1.10 Worry About Being a Victim1.11 Feeling Safe in City Facilities1.23 Feeling of Safety in Parks2. Strong Community Connections2.02 Customer Service Satisfaction2.04 City Website Satisfaction2.05 Online Services Satisfaction Rate2.15 Feeling Invited to Participate in City Decisions2.21 Satisfaction with Availability of City Information3. Quality of Life3.16 City Recreation, Arts, and Cultural Centers3.17 Community Services Programs3.19 Value of Special Events3.23 Right of Way Landscape Maintenance3.36 Quality of City Services4. Sustainable Growth & DevelopmentNo Performance Measures in this category presently relate directly to the Community Survey5. Financial Stability & VitalityNo Performance Measures in this category presently relate directly to the Community SurveyMethods:The survey is mailed to a random sample of households in the City of Tempe. Follow up emails and texts are also sent to encourage participation. A link to the survey is provided with each communication. To prevent people who do not live in Tempe or who were not selected as part of the random sample from completing the survey, everyone who completed the survey was required to provide their address. These addresses were then matched to those used for the random representative sample. If the respondent’s address did not match, the response was not used. To better understand how services are being delivered across the city, individual results were mapped to determine overall distribution across the city. Additionally, demographic data were used to monitor the distribution of responses to ensure the responding population of each survey is representative of city population. Processing and Limitations:The location data in this dataset is generalized to the block level to protect privacy. This means that only the first two digits of an address are used to map the location. When they data are shared with the city only the latitude/longitude of the block level address points are provided. This results in points that overlap. In order to better visualize the data, overlapping points were randomly dispersed to remove overlap. The result of these two adjustments ensure that they are not related to a specific address, but are still close enough to allow insights about service delivery in different areas of the city. The weighted data are used by the ETC Institute, in the final published PDF report.The 2023 Annual Community Survey report is available on data.tempe.gov or by visiting https://www.tempe.gov/government/strategic-management-and-innovation/signature-surveys-research-and-dataThe individual survey questions as well as the definition of the response scale (for example, 1 means “very dissatisfied” and 5 means “very satisfied”) are provided in the data dictionary.Additional InformationSource: Community Attitude SurveyContact (author): Adam SamuelsContact E-Mail (author): Adam_Samuels@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Data received from vendor after report is completedPublish Frequency: AnnualPublish Method: ManualData Dictionary

Abstract

The Jordan Population and Family Health Survey (JPFHS) is part of the worldwide Demographic and Health Surveys Program, which is designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 2012 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, mortality, family planning, and fertility preferences, as well as maternal and child health and nutrition, that can be used by program managers and policymakers to evaluate and improve existing programs. The JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional, or cross-national studies.

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The 2012 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and for the two special domains: the Badia areas and people living in refugee camps. To facilitate comparisons with previous surveys, the sample was also designed to produce estimates for the three regions (North, Central, and South). The grouping of the governorates into regions is as follows: the North consists of Irbid, Jarash, Ajloun, and Mafraq governorates; the Central region consists of Amman, Madaba, Balqa, and Zarqa governorates; and the South region consists of Karak, Tafiela, Ma'an, and Aqaba governorates.

The 2012 JPFHS sample was selected from the 2004 Jordan Population and Housing Census sampling frame. The frame excludes the population living in remote areas (most of whom are nomads), as well as those living in collective housing units such as hotels, hospitals, work camps, prisons, and the like. For the 2004 census, the country was subdivided into convenient area units called census blocks. For the purposes of the household surveys, the census blocks were regrouped to form a general statistical unit of moderate size (30 households or more), called a "cluster", which is widely used in surveys as a primary sampling unit (PSU).

Stratification was achieved by first separating each governorate into urban and rural areas and then, within each urban and rural area, by Badia areas, refugee camps, and other. A two-stage sampling procedure was employed. In the first stage, 806 clusters were selected with probability proportional to the cluster size, that is, the number of residential households counted in the 2004 census. A household listing operation was then carried out in all of the selected clusters, and the resulting lists of households served as the sampling frame for the selection of households in the second stage. In the second stage of selection, a fixed number of 20 households was selected in each cluster with an equal probability systematic selection. A subsample of two-thirds of the selected households was identified for anthropometry measurements.

Refer to Appendix A in the final report (Jordan Population and Family Health Survey 2012) for details of sampling weights calculation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2012 JPFHS used two questionnaires, namely the Household Questionnaire and the Woman’s Questionnaire (see Appendix D). The Household Questionnaire was used to list all usual members of the sampled households, and visitors who slept in the household the night before the interview, and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of the household, and marital status. In addition, questions were included on the socioeconomic characteristics of the household, such as source of water, sanitation facilities, and the availability of durable goods. Moreover, the questionnaire included questions about child discipline. The Household Questionnaire was also used to identify women who were eligible for the individual interview (ever-married women age 15-49 years). In addition, all women age 15-49 and children under age 5 living in the subsample of households were eligible for height and weight measurement and anemia testing.

The Woman’s Questionnaire was administered to ever-married women age 15-49 and collected information on the following topics: • Respondent’s background characteristics • Birth history • Knowledge, attitudes, and practice of family planning and exposure to family planning messages • Maternal health (antenatal, delivery, and postnatal care) • Immunization and health of children under age 5 • Breastfeeding and infant feeding practices • Marriage and husband’s background characteristics • Fertility preferences • Respondent’s employment • Knowledge of AIDS and sexually transmitted infections (STIs) • Other health issues specific to women • Early childhood development • Domestic violence

In addition, information on births, pregnancies, and contraceptive use and discontinuation during the five years prior to the survey was collected using a monthly calendar.

The Household and Woman’s Questionnaires were based on the model questionnaires developed by the MEASURE DHS program. Additions and modifications to the model questionnaires were made in order to provide detailed information specific to Jordan. The questionnaires were then translated into Arabic.

Anthropometric data were collected during the 2012 JPFHS in a subsample of two-thirds of the selected households in each cluster. All women age 15-49 and children age 0-4 in these households were measured for height using Shorr height boards and for weight using electronic Seca scales. In addition, a drop of capillary blood was taken from these women and children in the field to measure their hemoglobin level using the HemoCue system. Hemoglobin testing was used to estimate the prevalence of anemia.

Cleaning operations

Fieldwork and data processing activities overlapped. Data processing began two weeks after the start of the fieldwork. After field editing of questionnaires for completeness and consistency, the questionnaires for each cluster were packaged together and sent to the central office in Amman, where they were registered and stored. Special teams were formed to carry out office editing and coding of the openended questions.

Data entry and verification started after two weeks of office data processing. The process of data entry, including 100 percent reentry, editing, and cleaning, was done by using PCs and the CSPro (Census and Survey Processing) computer package, developed specially for such surveys. The CSPro program allows data to be edited while being entered. Data processing operations were completed by early January 2013. A data processing specialist from ICF International made a trip to Jordan in February 2013 to follow up on data editing and cleaning and to work on the tabulation of results for the survey preliminary report, which was published in March 2013. The tabulations for this report were completed in April 2013.

Response rate

In all, 16,120 households were selected for the survey and, of these, 15,722 were found to be occupied households. Of these households, 15,190 (97 percent) were successfully interviewed.

In the households interviewed, 11,673 ever-married women age 15-49 were identified and interviews were completed with 11,352 women, or 97 percent of all eligible women.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2012 Jordan Population and Family Health Survey (JPFHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2012 JPFHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2012 JPFHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulae. The computer

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

The metropolitan, urban and rural population and all .administrative regional units. as defined in Official Europe Union Statistics (NUTS 2) covered proportionately the respective population aged 18 and above. The country was divided into an appropriate number of areas, grouping NUTS regions at whatever level appropriately. The NUTS covered in Iceland were the following; Reykjavik, Near Reykjavik and Sudurnes, West-Iceland, North-Iceland, East-Iceland, South-Iceland.

The basic sample design was a multi-stage, random probability sample. 50 sampling points were drawn with probability proportional to population size, for a total coverage of the country. The sampling points were drawn after stratification by NUTS 2 region and by degree of urbanisation. They represented the whole territory of the country surveyed and are selected proportionally to the distribution of the population in terms of metropolitan, urban and rural areas. In each of the selected sampling points, one address was drawn at random. This starting address forms the first address of a cluster of a maximum of 20 addresses. The remainder of the cluster was selected as every Nth address by standard random route procedure from the initial address. In theory, there is no maximum number of addresses issued per country. Procedures for random household selection and random respondent selection are independent of the interviewer.s decision and controlled by the institute responsible. They should be as identical as possible from to country, full functional equivalence being a must.

At every address up to 4 recalls were made to attempt to achieve an interview with the selected respondent. There was only one interview per household. The final sample size is 489 completed interviews.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

The Australian Antarctic Division identified areas that required hydrographic surveying. (See map available in the download at \Plans and Instructions\HPS Supplied Data\davis_plan_2019_2020 version 5.1.pdf and a shapefile of the identified areas at FSD\ArcGIS\Pink V2\AOI_Unproject_wgs84.shp)

A team from the Maritime Geospatial Warfare Unit, of the Australian Hydrographic Service, was at Davis in early February 2020. Single beam and side scanning survey data was collected on the water, beach profiles collected and rock data.

Single beam and side scanning survey data Areas A, D, F, H, I, J and K were ice free. Area J was further broken down into four areas, J1, J2, J3 and J4. Areas A, D and F were thoroughly surveyed with 10m mainline spacing with 20m X-line spacing. Areas I, J3 and J4 were surveyed but due to time constraints were surveyed at approximately 40m line spacing to provide 200% sea floor coverage with the SSS to detect any features dangerous to navigation with one shoal detected in area I which is mentioned in Section I. Area H was too shallow to survey at any other time except high tide and it was decided to focus on other areas as the survey of this area would not value add to the required results of the survey. Area J1, J2 and K were not surveyed due to time constraints.

RTK corrections or access to the CORS network couldn't be made to the CEESCOPE survey system. Instead positioning during the survey was recorded exclusively with the NovaTel GNSS 850 Antenna. No post processing was conducted. The team wasn't able to determine why the CEESCOPE was unable to connect to the CORS network or Base Station to gain RTK corrections, despite considerable effort spent problem solving and conducting a number of trials. Tide data collected was applied to the data and all tidal information is explained in section F of the report.

A map showing the surveyed areas can be found in the report. Raw data in caris format is available from the Australian Hydrographic Office (AHO). Sounding data, stored as a shapefile, is available as a download file.

Beach profiles Sites were also surveyed with 5m line spacing to maximise seafloor coverage, at 5 beach locations, 4 in area A and 1 in Area F. ArcGIS projects and PDF documents displaying the depth data and significant rocks are included in the download. Please note the ArcGIS projects do not include the AHO chart, due to distribution restrictions on digital charts. It is included in the PDF documents. These documents refer to images taken from the survey boat and spreadsheets displaying gradients data.

Rock data A shapefile recording conspicuous rocks as well as photographs is available for downloading.

Bench mark positions were reclaimed using Trimble R10 and post processed with AUSPOS.

Abbreviations used in the download directories ROS = Report of Survey, FSD = Final Survey Data

A detailed report can be found at /ROS/

Projection……..…...…...………….….……..Universal Transverse Mercator (UTM) Zone 43 South Horizontal Datum……………………………World Geodetic System 1984 (WGS84) Vertical Datum…………………………….....Approximated Lowest Astronomical Tide (LAT) Sounding Depths.……………………………Metres (m)

Survey Date………………..………………….6th - 18th Feb 2020 Bathymetric Accuracy Horizontal……………± 0.8m Bathymetric Accuracy Vertical………………±0.46m Sounding Density……………………………..2m Surface Chart Reference………………………………AUS 451, 602​

ITRF 2014 and GRS80 were utilised for static observations of bench marks and levelling to the tide pole for establishment of approximate LAT. Hypack v19.1.11.0 which was used to gather all bathymetric data does not have the option to use the ITRF datum and the WGS84 Datum was used.

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project surveyed 34 features visible from the air to be used as ground control points (GCP) on the Outer Banks, North Carolina, on September 24 and 25, 2019, after the passing of Hurricane Dorian (U.S. landfall on September 6, 2019). Global Positioning System (GPS) data were collected in support of aerial imagery surveys documenting the storm impacts and subsequent recovery along the coast and will be used as control and check points in Structure-from-Motion (SfM) photogrammetry processing to produce topographic maps. This dataset consists of horizontal and vertical positions of permanent GCPs, measured using Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) equipment. The data are provided in comma-separated values (.csv) delimited text format, in both geographic and projected (Universal Transverse Mercator Zone 18N) coordinates, and vertical measurements are provided as both ellipsoid and orthometric heights. All horizontal coordinates and ellipsoid heights are referenced to the North American Datum of 1983 (NAD83(2011)), and orthometric heights are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B. Additional information as well as photographs for each GCP (120 photos were collected, in total) are also included.

This data release presents the post-processed Global Navigation Satellite System (GNSS) ground-survey data acquired during the installation of a camera system at Tres Palmas, Rincón, Puerto Rico (PR). The data contains topographic survey data collected during the installation of the camera. Data were collected on foot, by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying _location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) corrections referenced to a temporary base station located approximately 250 meters from the study area.