We include the course syllabus used to teach quantitative research design and analysis methods to graduate Linguistics students using a blended teaching and learning approach. The blended course took place over two weeks and builds on a face to face course presented over two days in 2019. Students worked through the topics in preparation for a live interactive video session each Friday to go through the activities. Additional communication took place on Slack for two hours each week. A survey was conducted at the start and end of the course to ascertain participants' perceptions of the usefulness of the course. The links to online elements and the evaluations have been removed from the uploaded course guide.Participants who complete this workshop will be able to:- outline the steps and decisions involved in quantitative data analysis of linguistic data- explain common statistical terminology (sample, mean, standard deviation, correlation, nominal, ordinal and scale data)- perform common statistical tests using jamovi (e.g. t-test, correlation, anova, regression)- interpret and report common statistical tests- describe and choose from the various graphing options used to display data- use jamovi to perform common statistical tests and graph resultsEvaluationParticipants who complete the course will use these skills and knowledge to complete the following activities for evaluation:- analyse the data for a project and/or assignment (in part or in whole)- plan the results section of an Honours research project (where applicable)Feedback and suggestions can be directed to M Schaefer schaemn@unisa.ac.za

Objective(s): Momentum for open access to research is growing. Funding agencies and publishers are increasingly requiring researchers make their data and research outputs open and publicly available. However, clinical researchers struggle to find real-world examples of Open Data sharing. The aim of this 1 hr virtual workshop is to provide real-world examples of Open Data sharing for both qualitative and quantitative data. Specifically, participants will learn: 1. Primary challenges and successes when sharing quantitative and qualitative clinical research data. 2. Platforms available for open data sharing. 3. Ways to troubleshoot data sharing and publish from open data. Workshop Agenda: 1. “Data sharing during the COVID-19 pandemic” - Speaker: Srinivas Murthy, Clinical Associate Professor, Department of Pediatrics, Faculty of Medicine, University of British Columbia. Investigator, BC Children's Hospital 2. “Our experience with Open Data for the 'Integrating a neonatal healthcare package for Malawi' project.” - Speaker: Maggie Woo Kinshella, Global Health Research Coordinator, Department of Obstetrics and Gynaecology, BC Children’s and Women’s Hospital and University of British Columbia This workshop draws on work supported by the Digital Research Alliance of Canada. Data Description: Presentation slides, Workshop Video, and Workshop Communication Srinivas Murthy: Data sharing during the COVID-19 pandemic presentation and accompanying PowerPoint slides. Maggie Woo Kinshella: Our experience with Open Data for the 'Integrating a neonatal healthcare package for Malawi' project presentation and accompanying Powerpoint slides. This workshop was developed as part of Dr. Ansermino's Data Champions Pilot Project supported by the Digital Research Alliance of Canada., NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on this page under "collaborate with the pediatric sepsis colab."

These are the data sets in machine readable files from a quantitative dye tracer test conducted at Langle Spring November 13-December 2, 2017 as part of the USGS training class, GW2227 Advanced Field Methods in Karst Terrains, held at the Savoy Experimental Watershed, Savoy Arkansas. Langle Spring is NWIS site 71948218, latitude 36.11896886, longitude -94.34548871. One pound of RhodamineWT dye was injected into a sinking stream at latitude 36.116772 longitude -94.341883 NAD83 on November 13, 2017 at 22:50. The data sets include original fluorimeter data logger files from Langle and Copperhead Springs, Laboratory Sectra-fluorometer files from standards and grab samples, and processed input and output files from the breakthrough curve analysis program Qtracer2 (Field, USEPA, 2002 EPA/600/R-02/001).

This data set contains the replication data and supplements for the article "Knowing, Doing, and Feeling: A three-year, mixed-methods study of undergraduates’ information literacy development." The survey data is from two samples: - cross-sectional sample (different students at the same point in time) - longitudinal sample (the same students and different points in time)Surveys were distributed via Qualtrics during the students' first and sixth semesters. Quantitative and qualitative data were collected and used to describe students' IL development over 3 years. Statistics from the quantitative data were analyzed in SPSS. The qualitative data was coded and analyzed thematically in NVivo. The qualitative, textual data is from semi-structured interviews with sixth-semester students in psychology at UiT, both focus groups and individual interviews. All data were collected as part of the contact author's PhD research on information literacy (IL) at UiT. The following files are included in this data set: 1. A README file which explains the quantitative data files. (2 file formats: .txt, .pdf)2. The consent form for participants (in Norwegian). (2 file formats: .txt, .pdf)3. Six data files with survey results from UiT psychology undergraduate students for the cross-sectional (n=209) and longitudinal (n=56) samples, in 3 formats (.dat, .csv, .sav). The data was collected in Qualtrics from fall 2019 to fall 2022. 4. Interview guide for 3 focus group interviews. File format: .txt5. Interview guides for 7 individual interviews - first round (n=4) and second round (n=3). File format: .txt 6. The 21-item IL test (Tromsø Information Literacy Test = TILT), in English and Norwegian. TILT is used for assessing students' knowledge of three aspects of IL: evaluating sources, using sources, and seeking information. The test is multiple choice, with four alternative answers for each item. This test is a "KNOW-measure," intended to measure what students know about information literacy. (2 file formats: .txt, .pdf)7. Survey questions related to interest - specifically students' interest in being or becoming information literate - in 3 parts (all in English and Norwegian): a) information and questions about the 4 phases of interest; b) interest questionnaire with 26 items in 7 subscales (Tromsø Interest Questionnaire - TRIQ); c) Survey questions about IL and interest, need, and intent. (2 file formats: .txt, .pdf)8. Information about the assignment-based measures used to measure what students do in practice when evaluating and using sources. Students were evaluated with these measures in their first and sixth semesters. (2 file formats: .txt, .pdf)9. The Norwegain Centre for Research Data's (NSD) 2019 assessment of the notification form for personal data for the PhD research project. In Norwegian. (Format: .pdf)

The Supplementary Material for this article:Supplementary Table 1 | PRISMA 2009 checklist.Supplementary Table 2 | Search strategies.Supplementary Table 3 | Research information details and indicators dataset.Supplementary Table 4 | Specific information of indicators and studies under different profile.Supplementary Table 5 | Analysis results data.

To address Toronto's 2012 budget gap of $774 million, City Council has launched a review of all of its services and implemented a multi-year financial planning process. This data set contains the responses to the multiple- choice questions on the Core Services Review Public Consultation Feedback Form from members of the public. Approximately 13,000 responses were received (full and partial). The consultation was held between May 11 and June 17, 2011. As a public consultation, respondents chose to participate, and chose which questions to answer. This produced a self-selected sample of respondents. The majority of the responses were from City of Toronto residents. There were some responses from GTA residents. City staff reviewed the data and removed personal information and input violating city policies (for example, contravenes the City's current anti-discrimination policy or confidentiality policy). The .SAV file may be viewed with Statistics software such as SPSS or SAS.

Abstract

This survey is the first detailed study on the phenomena of teacher absenteeism in Indonesia obtained from two unannounced visits to 147 sample schools in October 2002 and March 2003. The study was conducted by the SMERU Research Institute and the World Bank, affiliated with the Global Development Network (GDN). Similar surveys were carried out at the same time in seven other developing countries: Bangladesh, Ecuador, India, Papua New Guinea, Peru, Uganda, and Zambia.

This research focuses on primary school teacher absence rates and their relations to individual teacher characteristics, conditions of the community and its institutions, and the education policy at various levels of authority. A teacher was considered as absent if at the time of the visit the researcher could not find the sample teacher in the school.

This survey was conducted in randomly selected 10 districts/cities in four Indonesian regions: Java-Bali, Sumatera, Kalimantan-Sulawesi, and Nusa Tenggara.

Geographic coverage

Java-Bali, Sumatera, Kalimantan-Sulawesi and Nusa Tenggara regions

Analysis unit

• Teachers
• Schools

Kind of data

Sample survey data [ssd]

Sampling procedure

Information from Indonesian Statistics Agency (BPS) and the Ministry of Education was used as a basis to build a sample frame. The data gathered included the amount of total population, a list of villages and primary school facilities in each district/city. Due to limited time and resources, this research only focused on primary schools. In Indonesia, there are two types of primary education facilities: primary schools and primary madrasah. Primary schools are regulated by the Ministry of National Education, using the general curriculum, while primary madrasah are regulated by the Ministry of Religious Affairs, using a mixed (general and Islamic) curriculum.

A sample of districts/cities and schools (consisting of primary schools and primary madrasah) were selected using the following steps. First, Indonesia was divided into several regions based on the number of total population: Java-Bali, Sumatera, Kalimantan-Sulawesi, and Nusa Tenggara. Indonesian provinces that were suffering from various conflicts (such as Aceh, Central Sulawesi, Maluku, North Maluku, and Papua) were removed from the sample selection process. Then, from each region, a total of five districts and cities were randomly selected, taking into account the population of each district/city.

Second, 12 schools were selected in each district/city. Before choosing sampled schools, researchers randomly selected 10 villages in each district/city to be sampled, taking into account the location of these villages (in urban or rural areas). One of the 10 villages was a backup village to anticipate the possibility of a village that was too difficult to reach. In each village sampled, researchers asked residents about the location of primary schools/madrasah (both public and private) in these villages. They started visiting schools, giving priority to public primary schools/madrasahs. To meet the number of samples in each district/city, additional samples were selected from private schools.

Third, in each school sampled, the researcher would request a list of teachers. If a school visited was considered to be large, such as schools with more than 15 teachers, then the researcher would only interview 15 teachers chosen randomly to ensure that survey quality could be maintained despite the limited time and resources. Each school was visited twice, both on an unannounced date. From the 147 primary schools/madrasah in the sample, 1,441 teachers were selected in each visit (because this is a panel study, the teacher absence data that were used were taken only from teachers that could be interviewed or whose data were obtained from both visits). If there were teachers whose information was only obtained from one of the visits, then their data was not included in the dataset panel.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available:

• Teacher Questionnaire, First Visit
• Teacher Questionnaire, Second Visit.

Cleaning operations

Detailed information about data editing procedures is available in "Data Cleaning Guide for PETS/QSDS Surveys" in external resources.

The STATA cleaning do-file and the data quality report on the dataset can also be found in external resources.

Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

The two primary goals of this workshop are: (1) to present an example of working with data that uses one of the files available through the Data Liberation Initiative (DLI); and (2) to provide a hands-on computing exercise that introduces some basic approaches to quantitative analysis. The study chosen for this example is the National Survey of Literacy Skills Used in Daily Activities conducted in 1989. In completing this example, three general strategies for performing quantitative analysis will be discussed.

This data package includes a quantitative analysis of non-coral communities at sites along a water quality gradient off of Aua, American Samoa in 2022. These datasets were funded by the NOAA Coral Reef Conservation Program (CRCP) Project Number 31303 to study effects of land-based sources of pollution (LBSP) in Aua, American Samoa. In September 2022 Ecosystem Sciences Division (ESD) scientists of the Pacific Islands Fisheries Science Center (PIFSC) flew into American Samoa to survey 18 sites along a water quality gradient off of Aua. Three datasets are provided of the taxa species and counts of benthic foraminifera, benthic microalgae, and macroinvertebrates from samples collected between 9-28 September 2022. Samples were preserved in the field, and brought back to the NOAA Inouye Regional Center (IRC) and analyzed via microscopy. To analyze benthic foraminifera abundance, sediment samples were collected using a small sediment corer (60 ml syringe with the tip removed and a stopper placed there instead). Only the top 3 cm were retained. Under the microscope, benthic foraminifera were picked out of the sediment and identified. To analyze benthic microalgae, microscope slides were deployed on the seafloor at each site for 2 to 3 weeks. The benthic microalgae that settled was fixed and preserved in Lugol's solution and analyzed. Microalgae included diatoms (pennate and centric), dinoflagellates, chlorophyta, and cyanobacteria. To analyze macroinvertebrates: plastic scouring pads were deployed and attached to the substratum with zip-ties for 2 to 3 weeks. The scouring pads were removed after the settlement period, all plastic zip-ties and additional waste were removed from the reef. Macroinvertebrates that settled on the scouring pad were placed into sampling jars and fixed and preserved with 4% formalin, and subsequently analyzed under the microscope. These quantitative non-coral community surveys were one of several surveys conducted at the same sites across Aua reef in September 2022. Other surveys described and archived separately include surveys of water quality, CTD casts, coral demography, benthic imagery/benthic cover, and coral demography. These can be accessed under the 'Related Items' section of the InPort metadata record.

Objectives: In quantitative research, understanding basic parameters of the study population is key for interpretation of the results. As a result, it is typical for the first table (“Table 1”) of a research paper to include summary statistics for the study data. Our objectives are 2-fold. First, we seek to provide a simple, reproducible method for providing summary statistics for research papers in the Python programming language. Second, we seek to use the package to improve the quality of summary statistics reported in research papers.

Materials and Methods: The tableone package is developed following good practice guidelines for scientific computing and all code is made available under a permissive MIT License. A testing framework runs on a continuous integration server, helping to maintain code stability. Issues are tracked openly and public contributions are encouraged.

Results: The tableone software package automatically compiles summary statistics into publishable formats such...

The trends for sustainable lifestyle and marketing motivated natural product consumption, such as natural skin care products (NSCPs). Different personal, environmental, and sociocultural factors influence purchase intention (PI) for NSCPs. However, there is a lack of evidence on the role of consumers’ ethnicity in the PI model. The present study investigated the moderated mediation role of ethnicity in the relationship between related factors, including environmental concern, subjective norms, health factor, Halal certificate, packaging design, past experience factor, price factor, and PI mediated by personal attitude. A web-based survey was utilized to capture quantitative data from a random sample of 330 multicultural consumer group participants. The results of the study indicated that consumers’ ethnicity substantially moderated the mediation effect of personal attitude in the relationships between subjective norms, health factor, Halal certificate, packaging design, past experience factor, price factor, and PI in the model. The findings contributed to understanding of the factors that influenced the PI of consumers from diverse sociocultural contexts in the market for natural products. It contributed directly to natural product marketing and industry.

Example of dose-response data set. The data set contains dataused to quantitate the dose (concentration) response (effect) relationships for different stressors. The xlsx workbook contain the following sheets:

Introduction: Brief explanation to the qData template and example data set included

README: The README file provides an overview of the basic features of the qData template. The sheet contains overview of all columns in the qData template (and example), explanation to column title in the template, description for the column content, format of data, and an examples.

qData: the sheet contain the data for one stressor, External gamma radiation from a Cobalt-60 radiation source. Test species is duckweed, lemna minor. The column titles contain brief description to the content of the columns.

This is a dataset of participants responses to a survey questionnaire that was conducted as a part of a research paper. The study aims to examine the effect of decarbonization and energy efficiency in the Egyptian context in relation to pollution reduction, indoor and outdoor air quality which should reflect on human health and well-being. It also aims to assess carbon management strategies and policies adopted or needed in Egypt.

This dataset contains sample output data for TELL. The sample dataset includes four years of sample future data (2039, 2059, 2079, and 2099) that comes from IM3's future WRF runs under the RCP 8.5 climate scenario with SSP5 population forcing. Note that the GCAM-USA output used in this simulation is sample data only. As such the quantitative results from this set of sample output should not be considered valid.

This dataset includes all the data files that were used for the studies in my Master Thesis: "The Choice of Aspect in the Russian Modal Construction with prixodit'sja/prijtis'". The data files are numbered so that they are shown in the same order as they are presented in the thesis. They include the database and the code used for the statistical analysis. Their contents are described in the ReadMe files. The core of the work is a quantitative and empirical study on the choice of aspect by Russian native speakers in the modal construction prixodit’sja/prijtis’ + inf. The hypothesis is that in the modal construction prixodit’sja/prijtis’ + inf the aspect of the infinitive is not fully determined by grammatical context but, to some extent, open to construal. A preliminary analysis was carried out on data gathered from the Russian National Corpus (www.ruscorpora.ru). Four hundred and forty-seven examples with the verb prijtis' were annotated manually for several factors and a statistical test (CART) was run. Results demonstrated that no grammatical factor plays a big role in the use of one aspect rather than the other. Data for this study can be consulted in the files from 01 to 03 and include a ReadMe file, the database in .csv format and the code used for the statistical test. An experiment with native speakers was then carried out. A hundred and ten native speakers of Russian were surveyed and asked to evaluate the acceptability of the infinitive in examples with prixodit’sja/prijtis’ delat’/sdelat’ šag/vid/vybor. The survey presented seventeen examples from the Russian National Corpus that were submitted two times: the first time with the same aspect as in the original version, the second time with the other aspect. Participants had to evaluate each case by choosing among “Impossible”, “Acceptable” and “Excellent” ratings. They were also allowed to give their opinion about the difference between aspects in each example. A Logistic Regression with Mixed Effects was run on the answers. Data for this study can be consulted in the files from 04 to 010 and include a ReadMe file, the text and the answers of the questionnaire, the database in .csv, .txt and pdf formats and the code used for the statistical test. Results showed that prijtis’ often admits both aspects in the infinitive, while prixodit’sja is more restrictive and prefers imperfective. Overall, “Acceptable” and “Excellent” responses were higher than “Impossible” responses for both aspects, even when the aspect evaluated didn’t match with the original. Personal opinions showed that the choice of aspect often depends on the meaning the speaker wants to convey. Only in very few cases the grammatical context was considered to be a constraint on the choice.

This collection contains an example MINUTE-ChIP dataset to run minute pipeline on, provided as supporting material to help users understand the results of a MINUTE-ChIP experiment from raw data to a primary analysis that yields the relevant files for downstream analysis along with summarized QC indicators. Example primary non-demultiplexed FASTQ files provided here were used to generate GSM5493452-GSM5493463 (H3K27m3) and GSM5823907-GSM5823918 (Input), deposited on GEO with the minute pipeline all together under series GSE181241. For more information about MINUTE-ChIP, you can check the publication relevant to this dataset: Kumar, Banushree, et al. "Polycomb repressive complex 2 shields naïve human pluripotent cells from trophectoderm differentiation." Nature Cell Biology 24.6 (2022): 845-857. If you want more information about the minute pipeline, there is a public biorXiv and a GitHub repository and official documentation.

Abstract

This study examines various dimensions of primary health care delivery in Uganda, using a baseline survey of public and private dispensaries, the most common lower level health facilities in the country.

The survey was designed and implemented by the World Bank in collaboration with the Makerere Institute for Social Research and the Ugandan Ministries of Health and of Finance, Planning and Economic Development. It was carried out in October - December 2000 and covered 155 local health facilities and seven district administrations in ten districts. In addition, 1617 patients exiting health facilities were interviewed. Three types of dispensaries (both with and without maternity units) were included: those run by the government, by private for-profit providers, and by private nonprofit providers, mainly religious.

This research is a Quantitative Service Delivery Survey (QSDS). It collected microlevel data on service provision and analyzed health service delivery from a public expenditure perspective with a view to informing expenditure and budget decision-making, as well as sector policy.

Objectives of the study included: 1) Measuring and explaining the variation in cost-efficiency across health units in Uganda, with a focus on the flow and use of resources at the facility level; 2) Diagnosing problems with facility performance, including the extent of drug leakage, as well as staff performance and availability;
3) Providing information on pricing and user fee policies and assessing the types of service actually provided; 4) Shedding light on the quality of service across the three categories of service provider - government, for-profit, and nonprofit; 5) Examining the patterns of remuneration, pay structure, and oversight and monitoring and their effects on health unit performance; 6) Assessing the private-public partnership, particularly the program of financial aid to nonprofits.

Geographic coverage

The study districts were Mpigi, Mukono, and Masaka in the central region; Mbale, Iganga, and Soroti in the east; Arua and Apac in the north; and Mbarara and Bushenyi in the west.

Analysis unit

• local dispensary with or without maternity unit

Universe

The survey covered government, for-profit and nonprofit private dispensaries with or without maternity units in ten Ugandan districts.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey covered government, for-profit and nonprofit private dispensaries with or without maternity units in ten Ugandan districts.

The sample design was governed by three principles. First, to ensure a degree of homogeneity across sampled facilities, attention was restricted to dispensaries, with and without maternity units (that is, to the health center III level). Second, subject to security constraints, the sample was intended to capture regional differences. Finally, the sample had to include facilities in the main ownership categories: government, private for-profit, and private nonprofit (religious organizations and NGOs). The sample of government and nonprofit facilities was based on the Ministry of Health facility register for 1999. Since no nationwide census of for-profit facilities was available, these facilities were chosen by asking sampled government facilities to identify the closest private dispensary.

Of the 155 health facilities surveyed, 81 were government facilities, 30 were private for-profit facilities, and 44 were nonprofit facilities. An exit poll of clients covered 1,617 individuals.

The final sample consisted of 155 primary health care facilities drawn from ten districts in the central, eastern, northern, and western regions of the country. It included government, private for-profit, and private nonprofit facilities. The nonprofit sector includes facilities owned and operated by religious organizations and NGOs. Approximately one third of the surveyed facilities were dispensaries without maternity units; the rest provided maternity care. The facilities varied considerably in size, from units run by a single individual to facilities with as many as 19 staff members.

Ministry of Health facility register for 1999 was used to design the sampling frame. Ten districts were randomly selected. From the selected districts, a sample of government and private nonprofit facilities and a reserve list of replacement facilities were randomly drawn. Because of the unreliability of the register for private for-profit facilities, it was decided that for-profit facilities would be identified on the basis of information from the government facilities sampled. The administrative records for facilities in the original sample were first reviewed at the district headquarters, where some facilities that did not meet selection criteria and data collection requirements were dropped from the sample. These were replaced by facilities from the reserve list. Overall, 30 facilities were replaced.

The sample was designed in such a way that the proportion of facilities drawn from different regions and ownership categories broadly mirrors that of the universe of facilities. Because no nationwide census of for-profit health facilities is available, it is difficult to assess the extent to which the sample is representative of this category. A census of health care facilities in selected districts, carried out in the context of the Delivery of Improved Services for Health (DISH) project supported by the U.S. Agency for International Development (USAID), suggests that about 63 percent of all facilities operate on a for-profit basis, while government and nonprofit providers run 26 and 11 percent of facilities, respectively. This would suggest an undersampling of private providers in the survey. It is not clear, however, whether the DISH districts are representative of other districts in Uganda in terms of the market for health care.

For the exit poll, 10 interviews per facility were carried out in approximately 85 percent of the facilities. In the remaining facilities the target of 10 interviews was not met, as a result of low activity levels.

Sampling deviation

In the first stage in the sampling process, eight districts (out of 45) had to be dropped from the sample frame due to security concerns. These districts were Bundibugyo, Gulu, Kabarole, Kasese, Kibaale, Kitgum, Kotido, and Moroto.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available:

• District Health Team Questionnaire;
• District Facility Data Sheets;
• Uganda Health Facility Survey Questionnaire;
• Facility Data Sheets;
• Facility Patient Exit Poll Questionnaire.

The survey collected data at three levels: district administration, health facility, and client. In this way it was possible to capture central elements of the relationships between the provider organization, the frontline facility, and the user. In addition, comparison of data from different levels (triangulation) permitted cross-validation of information.

At the district level, a District Health Team Questionnaire was administered to the district director of health services (DDHS), who was interviewed on the role of the DDHS office in health service delivery. Specifically, the questionnaire collected data on health infrastructure, staff training, support and supervision arrangements, and sources of financing.

The District Facility Data Sheet was used at the district level to collect more detailed information on the sampled health units for fiscal 1999-2000, including data on staffing and the related salary structures, vaccine supplies and immunization activity, and basic and supplementary supplies of drugs to the facilities. In addition, patient data, including monthly returns from facilities on total numbers of outpatients, inpatients, immunizations, and deliveries, were reviewed for the period April-June 2000.

At the facility level, the Uganda Health Facility Survey Questionnaire collected a broad range of information related to the facility and its activities. The questionnaire, which was administered to the in-charge, covered characteristics of the facility (location, type, level, ownership, catchment area, organization, and services); inputs (staff, drugs, vaccines, medical and nonmedical consumables, and capital inputs); outputs (facility utilization and referrals); financing (user charges, cost of services by category, expenditures, and financial and in-kind support); and institutional support (supervision, reporting, performance assessment, and procurement). Each health facility questionnaire was supplemented by a Facility Data Sheet (FDS). The FDS was designed to obtain data from the health unit records on staffing and the related salary structure; daily patient records for fiscal 1999-2000; the type of patients using the facility; vaccinations offered; and drug supply and use at the facility.

Finally, at the facility level, an exit poll was used to interview about 10 patients per facility on the cost of treatment, drugs received, perceived quality of services, and reasons for using that unit instead of alternative sources of health care.

Cleaning operations

Detailed information about data editing procedures is available in "Data Cleaning Guide for PETS/QSDS Surveys" in external resources.

STATA cleaning do-files and the data quality reports on the datasets can also be found in external resources.

Abstract copyright UK Data Service and data collection copyright owner.

This study examined the ways in which home is conceptualised, experienced and evaluated by homeworkers, a hard-to-reach group. It explored the impact of homeworking on the experience of home and family life and sought to identify ways in which working from home may challenge the traditional stereotypical view of home. A pilot study suggested that the homeworking experience may be differentiated by economic, spatial and gender factors revealing potential tensions and inequalities among the broad range of people who work from home.

The research sought to: