Context

This is a demographic survey conducted by the market research department. The focus of this dataset is to have the customers' preferences regarding the computer brand.

Content

This dataset includes the CompleteResponses.csv that is the training split and SurveyIncomplete.csv for the test split. The training part consists of almost 10,000 answered surveys. The survey key is inside the survey_key.csv

We study the economic cost of dementia in Chile, and its variation according to socioeconomic status (SES). We use primary data from a survey of 330 informal primary caregivers who completed both a RUD-Lite and a socio-demographic questionnaire to evaluate the severity of dementia and caregiver’s burden. The costs of dementia are broken into three components: direct medical costs (medical care, drugs, tests); direct social costs (social service, daycare); and indirect costs (mostly associated to informal care). The average monthly cost per patient is estimated at US$ 1,463. Direct medical costs account for 20 per cent, direct social costs for 5 per cent and indirect costs for 75 per cent of the total cost. The mean monthly cost is found to be inversely related to SES, a pattern largely driven by indirect costs. The monthly cost for high SES is US$ 1,083 and US$ 1,588 for low SES. A multivariate regression analysis suggests that severity of dementia and caregiver’s burden account for between 49 and 70 per cent of the difference in the indirect cost across SES. However, between one-third and one-half of the variation across SES is not due to gradient in severity of dementia. Direct medical costs increase in higher SES, reflecting differences in purchasing power, while indirect costs are inversely related to SES and more than compensate differences in medical costs. Moreover, in lower SES groups, female caregivers, typically family members who are inactive in the labor market, mostly provide informal care. The average annual cost of dementia in Chile (US$ 17,559) is lower in comparison to high-income countries (US$ 39,595) and the proportion of cost related to informal cost is higher (74 per cent compared to 40 per cent). SES is a key determinant in the cost of dementia. In the absence of universal access to treatment, part of the social cost of dementia potentially preserves or increases income and gender inequality.

To facilitate the users of the data, a sample copy of the filled in data sheet is attached herewith for easy reference and understanding. The codes given to the questions in the data sheet is marked aside the questionnaire for easy identification. This is the supplementary document of interview schedule questions for the data published titled "Survey Data on Farmers Awareness, Perception towards Futures Market" The Interview Schedule includes demographic, training, farming, cost and marketing details of farmers. In addition, it also includes the questions measuring the awareness, and perception of farmers towards futures markets and ends with the details on information sources used by the farmers for taking pricing decisions.

Regression analysis of indirect costs of care (GLM model with log link).

Abstract

The Egypt Labor Market Panel Survey 2006 (ELMPS06) is the first full-fledged panel study of its scale in Egypt. This panel follows a nationally representative sample of 4,816 households visited in 1998, households that split from that sample, plus a refresher sample of 2,500 households. The total number of households reached in 2006 is 8,349. The ELMPS06 provides estimates of employment, unemployment and underemployment. The survey also collects information on job characteristics, mobility, and earnings. Collected data covers issues of household socio-economic characteristics, demographic characteristics, family enterprises and women’s status and work. A separate community level questionnaire has been administered to collect data on access to services and work opportunities in sampled localities. This report provides information on the different methodological issues related to the survey including sampling, questionnaire design, training of field staff, data collection, office review, and data entry.

Geographic coverage

The sample was designed to provide estimates of the indicators at the national level, for urban and rural areas, and for all regions.

Analysis unit

1- Households. 2- Individuals.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The ELMPS06 sample consists of three types of households: 1. Households visited in 1998 2. Split households 3. A refresher sample of 2,500 households In this section we describe in details the sampling techniques for both the 1998 and 2006 samples. We also describe the attrition to the 1998 sample due to loss of some household identification data, which were kept by CAPMAS.

The Selection Process of the 2006 New Sample This sample was selected from the CAPMAS 2005 Master Sample. This is a nationally representative two-stage self-weighted (to the extent possible) sample. Each governorate is allocated a number of PSUs in the master sample that is proportionate to its size and its urban/rural distribution.

The master sample was prepared through a two-stage process. First, shiekha's and villages are selected by probability proportionate-to-size method from two different sampling frames (one urban and another rural). In the second stage, these selected primary sample units are divided into secondary sampling units of 700 households each. A total of 1200 sampling units are then randomly selected to constitute the final master sample of CAPMAS. The ELMPS06 2006 new sample was proportionately selected from the CAPMAS master sample. Primary sampling units were then randomly selected from the CAPMAS master sample. Then within each PSU (containing 700 households in the master sample) we randomly selected 25 households. The 5,000 households that constitute the initial survey sample in 1998 were selected from a CAPMAS master sample prepared in 1995. The master sample consists of 750,000 households in 500 primary sampling units (PSUs) each consisting of 1,500 households. The CAPMAS master sample was selected through a two-stage process. The country is first divided into two strata: urban and rural. Each stratum is in turn divided into sub-strata representing each governorate. All the villages (in the case of rural strata) or shiyakhas (urban quarter, in the case of urban strata) in each substratum were listed and assigned a weight based on their population. The first stage consisted of choosing the villages and shiyakhas that would be represented in the sample based on the principal of probability proportional to size. This meant that a shiyakha or a village is possibly selected more than once if its size warrants that. The selected shiyakhas and villages are then divided into PSUs of approximately 1500 housing units each; then one or more PSUs are selected from each shiyakha or village. The selected PSUs were then re-listed in 1995 to enumerate all the households selected. As shown in Table 6, the master sample contains 306 urban PSUs and 194 rural PSUs.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaire design was finalized by the ERF team prior to the conclusion of the agreement between CAPMAS and ERF. The household-level research instruments comprise of three interrelated questionnaires for each household. The household questionnaire collects data on the different demographic characteristics of household members, household assets and access to services. This questionnaire also includes a module that tracks individuals who were part of the 1998 sample. The questionnaire allows space for 20 individuals as members of the household and for 10 splits. The individual questionnaire includes modules on the education and work characteristics for individuals six years and up. The printed version allows space for only five individuals, but more than one individual questionnaire can be used for a household depending on its size. The third questionnaire in the household-level research instrument is the “Migration, Family Enterprises and Non-wage Income” questionnaire, which includes the modules on migration, remittances, non-work-related income sources, and non-agricultural household enterprises.

----> Additions and changes to the 1998 Questionnaire

New sections were added to the 1998 questionnaires and a number of questions were deleted because they did not produce useful results after the analysis. The following are the major changes to the 1998 questionnaire: 1. The panel design mandated a number of changes, including the addition of a new section, Section 0.2, which gathered information on the basic characteristics of members who lived in household in1998 but no longer live in household in 2006 and their new addresses to track them. The cover page also included a question regarding the type of the household (whether it is originally visited in 1998, is a split household, or from the new sample). Section 0.1, the household roster, also included an additional question (0105), which inquires about the individual’s person number (pn) in the 1998 data set. Data collectors were able to get this information from the data sheets that were printed for each household containing basic demographic characteristics and a summary of her/his work and education characteristics. 2. Questions about land ownership and cultivation were added in section 0.3. Although they do not quite fit under housing and services, this was the best place to include them. Instructions during training were to write zero if no land was owned or rented by household. 3. The section on durable goods, section 0.4, now includes questions on whether the item was bought at the time of marriage and whether an item is bought to be used by a household member after she/he marries. 4. A short section on siblings (section 1.3) was added, which refers to total number of siblings, and whether or not they reside in the same household. 5. The section on education is expanded significantly. It now includes questions about the characteristics of secondary, preparatory, and primary schools, where relevant. Questions about repetitions and interruptions of schooling are included in order to gain better understanding of the number of years of schooling as opposed to grade level achieved and age of exit/completion. The section also allows one to assign a unique code for each school attended by the individual. These unique codes were received from the Ministry of Education and allow for analysis on school characteristics based on further data from the Ministry. 6. The migration section was moved earlier in the questionnaire so that it applies to all individuals whether they worked or not. In 1998, this section only applied to those who had previously worked. The section now applies to all those aged 15 and above. It also includes a new question about place of birth. 7. In the sections on work characteristics, we no longer have a reference week and a reference three months. We used instead the past seven days (counting back from day of first interview with individual) and the past three months. 8. In the unemployment section (Section 4.2), we added questions about the use of a landline or cell phones in job search activities. We also separated the question on registering with a government agency from the job search question. Now all the activities listed under job search are limited to the past three months reference period. 9. We separated the questions on subsistence and domestic work in a new section. These questions now apply to all children aged 6-17 and all women aged18-64, irrespective of employment status. The questions on domestic work are now much more detailed than before and ask about time spent on various domestic chores during the past 7 days. If the same amount of time is spent everyday, then interviewers were instructed to multiply the daily times by seven. However, this is designed to allow for variations in schedules every day. One of the reasons this section now applies to the past week rather than a reference week was that that it might be difficult to get an accurate estimate due to recall problems. Only the last question of the section allows for the activity to be done concurrently with other activities (child care). Otherwise, interviewers were instructed that they are enquiring about the time spent exclusively on the activity in question. 10. Questions about the “first job” were added into the section detecting employment in the forgoing three months. As in the job mobility section, to qualify as a job, the individual must have spent at least 6 months at the job. Thus, a job

Annual indirect cost of care by socioeconomic status with different methods*.

The "http://commons.trincoll.edu/aris/surveys/nsri-1990/" Target="_blank">National Survey of Religious Identification relates to a random digit-dialed telephone survey of 113,000 American households in the continental U.S. (48 states). The data was collected over a 13-month period by ICR Survey Research Group of Media, PA as part of their omnibus market research (EXCEL) survey. The prime question on the file is: What is your religion? If the initial answer was Protestant, there was a further question as to which denomination. The respondent is a randomly chosen (last birthday) adult over 18 years. Nineteen other socio-demographic questions are attached to this. The NSRI makes a significant contribution by presenting a large sample size reflecting the true richness of the country's religious tapestry and the national coverage necessary to provide high quality statistics on what is actually happening around us.

These surveys were undertaken to measure changes in consumer attitudes and expectations, to understand why these changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. This type of information is essential for forecasting changes in aggregate consumer behavior. Since the late 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter. Each monthly survey probes a different aspect of consumer confidence. Open-ended questions are asked concerning evaluations and expectations about personal finances, employment, price changes, and the national business situation. Additional questions probe buying intentions for automobiles and the respondent's appraisals of present market conditions for purchasing houses, automobiles, and other durables. Demographic information includes ethnic origin, sex, age, and education.

A 69-question survey instrument was developed by the study authors. Questions were selected based on the beliefs, values, and experiences shared by MLM participants in four focus groups conducted in an earlier phase of the research, and also on previous literature describing the characteristics of individuals and communities exposed to MLM. The survey was administered to participants belonging to the GfK KnowledgePanel, the largest online panel that uses probability-based sampling techniques for recruiting a nationally-representative sample of Americans. This sampling frame allows researchers to produce statistically valid estimates that are generalizable to the U.S. population.

The survey consisted of two phases: 1) initial screening of 7,949 KnowledgePanel members to calculate lifetime prevalence of MLM in the United States; and 2) the main survey with study-eligible respondents aged 18 years and older. Qualifying respondents who participated in phase 2 included 601 KnowledgePanel members who were distributors for an MLM firm sometime in the past (adopters), and 415 KnowledgePanel members who never participated in MLM before (non-adopters). Sample size quotas of 600 MLM participants and 400 non-participants were set a priori, although more panel members were screened into the survey to accommodate for case deletions due to response error and missing data.

For the 601 respondents who previously participated or currently work as distributors with an MLM firm, the survey instrument asked detailed questions about the first MLM firm they ever joined. They were asked to identify the name of the MLM company from a dropdown list (or free entry), who recruited them, the reasons why they joined, the average number of hours they worked each week, how long they maintained their membership, how much money they spent on inventory, training, and marketing materials, whether they made a profit, broke even, or lost money, and whether they felt the company accurately represented their chances of achieving financial success. The survey also gathered information on these adopters’ life circumstances, household income, age and employment prior to joining, and their reasons for leaving the MLM company if they were no longer active. They were also asked how many MLM companies they have joined in their lifetime and if they were currently working as a distributor for an MLM firm.

The 415 respondents who said they have never joined an MLM firm were asked if anyone had ever asked them to join, and if so, to select one or more reasons for why they declined. Both groups were asked demographic, economic, mindset, and social activity questions.

The dataset contains several components, including: 1. The survey instrument used to collect the data in .pdf file format (pdf file for the questionnaire) 2. The raw survey data in .csv file format (csv file for survey data): The survey data contains 251 variables with responses from 1002 respondents. In the survey design, all questions are mandatory, and therefore no missing values exist, except for instances where respondents chose to respond with “prefer not to say” (in some sensitive demographic questions) or “I don’t know” (in some questions related to their social networks). Non-applicable responses are coded as "NULL" and blank values. 3. The codebook for the raw survey data in .xlsx file format (xlsx file for survey data): The codebook explains each of the 251 variables included in the survey data file. The codebook lists how each survey question and response option is numerically coded in the raw data and can be used as a guide for navigating the survey dataset. 4. The product feature list data in .csv file format (csv file for product data): The product feature list data contains the product features of 624 vacuum cleaner products and each product has 32 variables/features. Missing values, where no online information is available, are coded as “NA,” while non-applicable values, such as runtime for corded vacuum cleaners or navigation path for non-robotic vacuum cleaners, are coded as blank values. 5. The codebook for the product features list data in .xlsx file format (xlsx file for product data): The accompanying codebook provides a detailed description of each feature and its data type, as well as the number of missing values for each product feature in the last column.

The questionnaire is provided as a supplementary file. Only the completed questionnaires were used in the analysis. Participation in the study was voluntary and anonymous. The structure of the questionnaire used for data collection includes 3 sections, Demographic questions, General / Basic questions related to contact lens use and Questions about the infection risk, views, rumours and the possible impact or not of the Covid-19 pandemic on the contact lens use, during the period of the first lockdown in Greece (23 March- 4 May 2020). Each section consists of closed-ended question types, multiple-choice, 5-point Likert scale, dichotomous questions and Question Skip Logic. In the survey, 1676 individuals participated in which 1037 individuals were contact lens users and completed the questionnaire. The 76.7% (795 ) were Female and 23.3% (242 ) were Male.

Annual Household income per capita and population share by socioeconomic status*.

The aim of LAMO (Labourmarket Monitoring) is the development, application and validation of a monitoring tool for the regular survey of the changes on the labour market in the course of the EU enlargement. Another goal is to complement the objective labour market data with information on the subjective willingness of people in the border regions to commute between home and work or to emigrate. Thereby, developments can assessed and this enables politics to react accordingly in time. The need for labour force in the regions is evaluated so that the whole labour market situation can be considered. The LAMO tools are expert interviews, household and enterprise interviews. The household interview questions are on the following topics:->socio-demographic questions, qualification and knowledge, occupational situation, salary expectations, flexibility concerning job and living, experiences with working abroad, experiences with commuting between home and work within the own country, willingness and reasons for working abroad or to emigrate, etc.

Abstract

The Integrated Household Survey is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO) roughly every 3-5 years to monitor and evaluate the changing conditions of Malawian households. The IHS data have, among other insights, provided benchmark poverty and vulnerability indicators to foster evidence-based policy formulation and monitor the progress of meeting the Millennium Development Goals (MDGs), the goals listed as part of the Malawi Growth and Development Strategy (MGDS) and now the Sustainable Development Goals (SDGs).

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Consumption expenditure commodities/items
• Communities
• Agricultural household/ Holder/ Crop
• Market

Universe

Members of the following households are not eligible for inclusion in the survey: • All people who live outside the selected EAs, whether in urban or rural areas. • All residents of dwellings other than private dwellings, such as prisons, hospitals and army barracks. • Members of the Malawian armed forces who reside within a military base. (If such individuals reside in private dwellings off the base, however, they should be included among the households eligible for random selection for the survey.) • Non-Malawian diplomats, diplomatic staff, and members of their households. (However, note that non-Malawian residents who are not diplomats or diplomatic staff and are resident in private dwellings are eligible for inclusion in the survey. The survey is not restricted to Malawian citizens alone.) • Non-Malawian tourists and others on vacation in Malawi.

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHS5 sampling frame is based on the listing information and cartography from the 2018 Malawi Population and Housing Census (PHC); includes the three major regions of Malawi, namely North, Center and South; and is stratified into rural and urban strata. The urban strata include the four major urban areas: Lilongwe City, Blantyre City, Mzuzu City, and the Municipality of Zomba. All other areas are considered as rural areas, and each of the 27 districts were considered as a separate sub-stratum as part of the main rural stratum. The sampling frame further excludes the population living in institutions, such as hospitals, prisons and military barracks. Hence, the IHS5 strata are composed of 32 districts in Malawi.

A stratified two-stage sample design was used for the IHS5.

Note: Detailed sample design information is presented in the "Fifth Integrated Household Survey 2019-2020, Basic Information Document" document.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

HOUSEHOLD QUESTIONNAIRE The Household Questionnaire is a multi-topic survey instrument and is near-identical to the content and organization of the IHS3 and IHS4 questionnaires. It encompasses economic activities, demographics, welfare and other sectoral information of households. It covers a wide range of topics, dealing with the dynamics of poverty (consumption, cash and non-cash income, savings, assets, food security, health and education, vulnerability and social protection). Although the IHS5 household questionnaire covers a wide variety of topics in detail it intentionally excludes in-depth information on topics covered in other surveys that are part of the NSO’s statistical plan (such as maternal and child health issues covered at length in the Malawi Demographic and Health Survey).

AGRICULTURE QUESTIONNAIRE All IHS5 households that are identified as being involved in agricultural or livestock activities were administered the agriculture questionnaire, which is primarily modelled after the IHS3 counterpart. The modules are expanding on the agricultural content of the IHS4, IHS3, IHS2, AISS, and other regional agricultural surveys, while remaining consistent with the NACAL topical coverage and methodology. The development of the agriculture questionnaire was done with input from the aforementioned stakeholders who provided input on the household questionnaire as well as outside researchers involved in research and policy discussions pertaining to the Malawian agriculture. The agriculture questionnaire allows, among other things, for extensive agricultural productivity analysis through the diligent estimation of land areas, both owned and cultivated, labor and non-labor input use and expenditures, and production figures for main crops, and livestock. Although one of the major foci of the agriculture data collection effort was to produce smallholder production estimates for major crops, it is also possible to disaggregate the data by gender and main geographical regions. The IHS5 cross-sectional households supply information on the last completed rainy season (2017/2018 or 2018/2019) and the last completed dry season (2018 or 2019) depending on the timing of their interview.

FISHERIES QUESTIONNAIRE The design of the IHS5 fishery questionnaire is identical to the questionnaire designed for IHS3. The IHS3 fisheries questionnaire was informed by the design and piloting of a fishery questionnaire by the World Fish Center (WFC), which was supported by the LSMS-ISA project for the purpose of assembling a fishery questionnaire that could be integrated into multi-topic household-surveys. The WFC piloted the draft instrument in November 2009 in the Lower Shire region, and the NSO team considered the revised draft in designing the IHS5 fishery questionnaire.

COMMUNITY QUESTIONNAIRE The content of the IHS5 Community Questionnaire follows the content of the IHS3 & IHS4 Community Questionnaires. A “community” is defined as the village or urban location surrounding the enumeration area selected for inclusion in the sample and which most residents recognize as being their community. The IHS5 community questionnaire was administered to each community associated with the cross-sectional EAs interviewed. Identical to the IHS3 and IHS4 approach, to a group of several knowledgeable residents such as the village headman, the headmaster of the local school, the agricultural field assistant, religious leaders, local merchants, health workers and long-term knowledgeable residents. The instrument gathers information on a range of community characteristics, including religious and ethnic background, physical infrastructure, access to public services, economic activities, communal resource management, organization and governance, investment projects, and local retail price information for essential goods and services.

MARKET QUESTIONNAIRE The Market Survey consisted of one questionnaire which is composed of four modules. Module A: Market Identification, Module B: Seasonal Main Crops, Module C: Permanents Crops, and Module D: Food Consumption.

Cleaning operations

DATA ENTRY PLATFORM To ensure data quality and timely availability of data, the IHS5 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHS5, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Lenovo tablet computer. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. In Survey Solutions, Headquarters can then see the location of the dwellings plotted on a map of Malawi to better enable supervision from afar – checking both the number of interviews performed and the fact that the sample households lie within EA boundaries. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (NSO management) assigned work to supervisors based on their regions of coverage. Supervisors then made assignments to the enumerators linked to their Supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHS5 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to STATA for other consistency checks, data cleaning, and analysis.

DATA MANAGEMENT The IHS5 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHS5 Interviews were collected in “sample” mode (assignments generated from headquarters) as opposed to “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. Prior programming of the data

Determinants of the total cost. Regression analysis of total annual costs of care (GLM model with log link).

Introduction

RetailMax, a nationwide retail chain selling electronics, home goods, and apparel, operates through multiple channels: physical stores, an e-commerce website, and a mobile app.

The executive team needs answers to critical business questions:

1. Which sales channels are most profitable by product category?
2. How do customer purchasing patterns differ across channels?
3. What is the impact of promotions on sales across different channels?
4. Which stores are underperforming relative to their regional benchmarks?
5. How does seasonal variation affect product category performance?

The Data Architecture

To answer these questions, we need a well-structured database with interconnected tables:

Products, Categories, Subcategories: Product information including pricing and cost data

Sales: Transaction details including channel, store, customer, and promotion information

Channels: Different sales platforms (In-Store, Website, Mobile App, etc.)

Stores and Regions: Physical location information

Customers: Customer demographics and preferences

Promotions: Marketing campaign details

This study examined attitudes toward work and family integration across generations and was conducted by the Radcliffe Public Policy Center with Harris Interactive Inc., a market research firm. The focus was on various aspects of the employment experience, including job satisfaction, employee loyalty, flexible scheduling, and employer policies, and on family life, including responsibilities for child and elder care, priority of family time, and gender roles within the family. The survey was conducted by telephone between January and February of 2000. A nationally representative sample selected by random digit dialing of 1,008 adults aged 21 and older participated in the study. Respondents were screened to determine their employment status. Those who were currently employed or had worked in the past on either a part- or full-time basis were considered eligible. Of the 1,008 participants, 699 were currently employed. Survey questions included family responsibilities, expectations of spouses/partners, gender roles, career plans, financial and employment security, and employment satisfaction and experiences, including the availability of various job benefits and policies. The survey also included basic demographic information on the respondent and her/his household. The Murray Research Archive holds numeric file data from this study. Follow-up of the participants is not possible.

Socio-demographic and clinical characteristics of the patients and caregivers*.

Caregivers and patients wellbeing by socioeconomic status*.