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Survey sampling

About: Survey sampling is a research topic. Over the lifetime, 2686 publications have been published within this topic receiving 98096 citations.


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Book
01 Aug 1984
TL;DR: This chapter discusses ethical issues in Survey Research, as well as methods of data collection and analysis, and types of error in Surveys.
Abstract: Preface 1. Introduction Reasons for Surveys The Components of Surveys Purposes and Goals of This Text 2. Sampling The Sample Frame Selecting a One-Stage Sample Multistage Sampling Making Estimates From Samples and Sampling Errors How Big Should a Sample Be? Sampling Error as a Component of Total Survey Error Exercise 3. Nonresponse: Implementing a Sample Design Calculating Response Rates Bias Associated With Nonresponse Reducing Nonresponse in Telephone or Personal Interview Surveys Reducing Nonresponse to Mail Surveys Reducing Nonresponse to Internet Surveys Multimode Data Collection Correcting for Nonresponse Nonprobability (or Modified Probability) Samples Nonresponse as a Source of Error Exercise 4. Methods of Data Collection Major Issues in Choosing a Strategy Summary Comparison of Methods Conclusion Exercise 5. Designing Questions to Be Good Measures Increasing the Reliability of Answers Avoiding Multiple Questions Types of Measures/Types of Questions Increasing the Validity of Factual Reporting Increasing the Validity of Answers Describing Subjective States Question Design and Error Exercises 6. Evaluating Survey Questions and Instruments Defining Objectives Preliminary Question Design Steps Presurvey Evaluation Design, Format, and Layout of Survey Instruments Field Pretests Survey Instrument Length Conclusion Exercise 7. Survey Interviewing Overview of Interviewer Job Interviewer Recruitment and Selection Training Interviewers Supervision Survey Questions Interviewing Procedures Validation of Interviews The Role of Interviewing in Survey Error Exercise 8. Preparing Survey Data for Analysis Formatting a Data File Constructing a Code Approaches to Coding and Data Entry Data Cleaning Coding and Data Reduction as Sources of Errors in Surveys 9. Ethical Issues in Survey Research Informing Respondents Protecting Respondents Benefits to Respondents Ethical Responsibilities to Interviewers Conclusion 10. Providing Information About Survey Methods Exercise 11. Survey Error in Perspective The Concept of Total Survey Design Error in Perspective Conclusion References Index About the Author

5,784 citations

Journal ArticleDOI
TL;DR: It is concluded that the choice of the techniques (Convenience Sampling and Purposive Sampling) depends on the nature and type of the research.
Abstract: This article studied and compared the two nonprobability sampling techniques namely, Convenience Sampling and Purposive Sampling. Convenience Sampling and Purposive Sampling are Nonprobability Sampling Techniques that a researcher uses to choose a sample of subjects/units from a population. Although, Nonprobability sampling has a lot of limitations due to the subjective nature in choosing the sample and thus it is not good representative of the population, but it is useful especially when randomization is impossible like when the population is very large. It can be useful when the researcher has limited resources, time and workforce. It can also be used when the research does not aim to generate results that will be used to create generalizations pertaining to the entire population. Therefore, there is a need to use nonprobability sampling techniques. The aim of this study is to compare among the two nonrandom sampling techniques in order to know whether one technique is better or useful than the other. Different articles were reviewed to compare between Convenience Sampling and Purposive Sampling and it is concluded that the choice of the techniques (Convenience Sampling and Purposive Sampling) depends on the nature and type of the research.

4,956 citations

Journal ArticleDOI
TL;DR: A new variant of chain-referral sampling, respondent-driven sampling, is introduced that employs a dual system of structured incentives to overcome some of the deficiencies of such samples and discusses how respondent- driven sampling can improve both network sampling and ethnographic investigation.
Abstract: A population is “hidden” when no sampling frame exists and public acknowledgment of membership in the population is potentially threatening. Accessing such populations is difficult because standard probability sampling methods produce low response rates and responses that lack candor. Existing procedures for sampling these populations, including snowball and other chain-referral samples, the key-informant approach, and targeted sampling, introduce well-documented biases into their samples. This paper introduces a new variant of chain-referral sampling, respondent-driven sampling, that employs a dual system of structured incentives to overcome some of the deficiencies of such samples. A theoretic analysis, drawing on both Markov-chain theory and the theory of biased networks, shows that this procedure can reduce the biases generally associated with chain-referral methods. The analysis includes a proof showing that even though sampling begins with an arbitrarily chosen set of initial subjects, as do most chain-referral samples, the composition of the ultimate sample is wholly independent of those initial subjects. The analysis also includes a theoretic specification of the conditions under which the procedure yields unbiased samples. Empirical results, based on surveys of 277 active drug injectors in Connecticut, support these conclusions. Finally, the conclusion discusses how respondent- driven sampling can improve both network sampling and ethnographic 44 investigation.

3,950 citations

Book
22 May 1997
TL;DR: This book presents the principles of Estimation for Finite Populations and Important Sampling Designs and a Broader View of Errors in Surveys: Nonsampling Errors and Extensions of Probability Sampling Theory.
Abstract: PART I: Principles of Estimation for Finite Populations and Important Sampling Designs: Survey Sampling in Theory and Practice. Basic Ideas in Estimation from Probability Samples. Unbiased Estimation for Element Sampling Designs. Unbiased Estimation for Cluster Sampling and Sampling in Two or More Stages. Introduction to More Complex Estimation Problems.- PART II: Estimation through Linear Modeling, Using Auxiliary Variables: The Regression Estimator. Regression Estimators for Element Sampling Designs. Regression Estimators for Cluster Sampling and Two-Stage Sampling.- PART III: Further Questions in Design and Analysis of Surveys: Two-Phase Sampling. Estimation for Domains. Variance Estimation. Searching for Optimal Sampling Designs. Further Statistical Techniques for Survey Data.- PART IV: A Broader View of Errors in Surveys: Nonsampling Errors and Extensions of Probability Sampling Theory. Nonresponse. Measurement Errors. Quality Declarations for Survey Data.- Appendix A - D.- References.

3,197 citations

Book
01 Jan 1973
TL;DR: The Logic of Survey Sampling and the Logic of Probability Sampling, a comparison of Survey and Other Methods, and the Ethics of Survey Research, a review of social science research in the 21st Century.
Abstract: PART I. THE SCIENTIFIC CONTEXT OF SURVEY RESEARCH. 1. The Logic of Science. The Traditional Perspective. The Debunking of Science. Science in Practice. What is Science? 2. Science and Social Science. The Search for Social Regularities. The Characteristics of Social Science. Methods of Social Scientific Research. 3. Survey Research as a Method of Social Science. A Brief History of Survey Research. The Scientific Characteristics of Survey Research. A Comparison of Survey and Other Methods. Is Survey Research Really Scientific? PART II. SURVEY RESEARCH DESIGN. 4. Types of Study Design. Purposes of Survey Research. Units of Analysis. Basic Survey Designs. Variations on Basic Designs. Choosing the Appropriate Design. 5. The Logic of Survey Sampling. The Logic of Probability Sampling. Sampling Concepts and Terminology. Probability Sampling Theory and Sampling. Distribution. Populations and Sampling Frames. Types of Sampling Designs. Disproportionate Sampling and Weighting. Nonprobability Sampling. Nonsurvey Uses of Sampling Methods. 6. Examples of Sample Designs. Sampling University Students. Sampling Medical School Faculty. Sampling Episcopal Churchwomen. Sampling Oakland Households. 7. Conceptualization and Instrument Design. Logic of Conceptualization. An Operationalization Framework. Types of Data. Levels of Measurement. Guides to Question Construction. Measurement Quality. General Questionnaire Format. Ordering Questions in a Questionnaire. Instructions. Reproducing the Questionnaire. 8. Index and Scale Construction. Indexes Versus Scales. Index Construction. Scale Construction. Typologies. PART III. DATA COLLECTION. 9. Self-Administered Questionnaires. Mail Distribution and Return. Postal Options and Relative Costs. Monitoring Returns. Follow-up Mailings. Acceptable Response Rates. A Case Study. 10. Interview Surveys. Imporance of Interviewer. General Rules for Interviewing. Interviewer Training. The Interviewing Operation. 11. Data Processing. Computers in Survey Research. Coding. Codebook Construction. Coding and Data Entry Options. Precoding for Data Entry. Data Cleaning. 12. Pretests and Pilot Studies. Conducting Pretests. Conducting Pilot Studies. Evaluating Pretests and Pilot Studies. PART IV. SURVEY RESEARCH ANALYSIS. 13. The Logic of Measurement and Association. The Traditional Image. The Interchangeability of Indexes. Implications. 14. Constructing and Understanding Tables. Univariate Analysis. Subgroup Descriptions. Bivariate Analysis. Multivariate Analysis. 15. The Elaboration Model. History of the Elaboration Model. The Elaboration Paradigm. Elaboration and Ex Post Facto Hypothesizing. 16. Social Statistics. Descriptive Statistics. Inferential Statistics. 17. Advanced Multivariate Techniques. Regression Analysis. Path Analysis. Factor Analysis. Analysis of Variance. Discriminant Analysis. Log-Linear Models. 18. The Reporting of Survey Research. Some Basic Considerations. Organization of the Reports. Guidelines for Reporting Analysis. PART V. SURVEY RESEARCH IN SOCIAL CONTEXT. 19. The Ethics of Survey Research. Voluntary Participation. No Harm to Respondents. Anonymity and Confidentiality. Identifying Purpose and Sponsor. Analysis and Reporting. A Professional Code of Ethics. Ethics -- Relevant Illustrations. 20. The Informed Survey Research Consumer. Research Design. Measurement. Sampling. Data Analysis. Data Reporting. APPENDICES. Appendix A. Table of Random Numbers. Appendix B. Estimated Sampling Error for a Binomial (95% Confidence Level). Appendix C. Distribution of Chi Square. Appendix D. Normal Curve Areas.

2,364 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20238
202238
202167
202078
201965
201876