Lars E. Lyberg

Introduction to Survey Quality

Preface. Chapter 1. The Evolution of Survey Process Quality. 1.1 The Concept of a Survey. 1.2 Types of Surveys. 1.3 Brief History of Survey Methodology. 1.4 The Quality Revolution. 1.5 Definitions of Quality and Quality in Statistical Organizations. 1.6 Measuring Quality. 1.7 Improving Quality. 1.8 Quality in a Nutshell. Chapter 2. The Survey Process and Data Quality. 2.1 Overview of the Survey Process. 2.2 Data Quality and Total Survey Error. 2.3 Decomposing Nonsampling Error into Its Component Parts. 2.4 Gauging the Magnitude of Total Survey Error. 2.5 Mean Squared Error. 2.6 An Illustration of the Concepts. Chapter 3. Coverage and Nonresponse Error. 3.1 Coverage Error. 3.2 Measures of Coverage Bias. 3.3 Reducing Coverage Bias. 3.4 Unit Nonresponse Error. 3.5 Calculating Response Rates. 3.6 Reducing Nonresponse Bias. Chapter 4. The Measurement Process and Its Implications for Questionnaire Design. 4.1Components of Measurement Error. 4.2 Errors Arising from the Questionnaire Design. 4.3 Understanding the Response Process. Chapter 5. Errors Due to Interviewers and Interviewing. 5.1 Role of the Interviewer. 5.2 Interviewer Variability. 5.3 Design Factors that Influence Interviewer Effects. 5.4 Evaluation of Interviewer Performance. Chapter 6. Data Collection Modes and Associated Errors. 6.1 Modes of Data Collection. 6.2 Decision Regarding Mode. 6.3 Some Examples of Mode Effects. Chapter 7. Data Processing: Errors and Their Control. 7.1 Overview of Data Processing Steps. 7.2 Nature of Data Processing Error. 7.3 Data Capture Errors. 7.4 Post-Data Capture Editing. 7.5 Coding. 7.6 File Preparation. 7.7 Applications of Continuous Quality Improvement: The Case of Coding. 7.8 Integration Activities. Chapter 8. Overview of Survey Error Evaluation Methods. 8.1 Purposes of Survey Error Evaluation. 8.2 Evaluation Methods for Designing and Pretesting Surveys. 8.3 Methods for Monitoring and Controlling Data Quality. 8.4 Postsurvey Evaluations. 8.5 Summary of Evaluation Methods. Chapter 9. Sampling Error. 9.1 Brief History of Sampling. 9.2 Nonrandom Sampling Methods. 9.3 Simple Random Sampling. 9.4 Statistical Inference in the Presence of Nonsampling Errors. 9.5 Other Methods of Random Sampling. 9.6 Concluding Remarks. Chapter 10.1 Practical Survey Design for Minimizing Total Survey Error. 10.1 Balance Between Cost, Survey Error, and Other Quality Features. 10.2 Planning a Survey for Optimal Quality. 10.3 Documenting Survey Quality. 10.4 Organizational Issues Related to Survey Quality. References. Index.

Measurement Errors in Surveys.

Partial table of contents: THE QUESTIONNAIRE. The Current Status of Questionnaire Design (N. Bradburn & S. Sudman). Context Effects in the General Social Survey (T. Smith). RESPONDENTS AND RESPONSES. Recall Error: Sources and Bias Reduction Techniques (D. Eisenhower, et al.). Toward a Response Model in Establishment Surveys (W. Edwards & D. Cantor). INTERVIEWERS AND OTHER MEANS OF DATA COLLECTION. The Design and Analysis of Reinterview: An Overview (G. Forsman & I. Schreiner). Expenditure Diary Surveys and Their Associated Errors (A. Silberstein & S. Scott). MEASUREMENT ERRORS IN THE INTERVIEW PROCESS. Cognitive Laboratory Methods: A Taxonomy (B. Forsyth & J. Lessler). The Effect of Interviewer and Respondent Characteristics on the Quality of Survey Data: A Multilevel Model (J. Hox, et al.). MODELING MEASUREMENT ERRORS AND THEIR EFFECTS ON ESTIMATION AND DATA ANALYSIS. Approaches to the Modeling of Measurement Errors (P. Biemer & S. Stokes). Evaluation of Measurement Instruments Using a Structural Modeling Approach (W. Saris & F. Andrews). Chi-Squared Tests with Complex Survey Data Subject to Misclassification Error (J. Rao & D. Thomas). References. Index.

Survey measurement and process quality

Partial table of contents: QUESTIONNAIRE DESIGN. From Theoretical Concept to Survey Question (J. Hox). Designing Rating Scales for Effective Measurement in Surveys (J. Krosnick & L. Fabrigar). DATA COLLECTION. Developing a Speech Recognition Application for Survey Research (B. Blyth). Children as Respondents: Methods for Improving Data Quality (J. Scott). POST SURVEY PROCESSING AND OPERATIONS. Integrated Control Systems for Survey Processing (J. Bethlehem). QUALITY ASSESSMENT AND CONTROL. Continuous Quality Improvement in Statistical Agencies (D. Morganstein & D. Marker). ERROR EFFECTS ON ESTIMATION, ANALYSES, AND INTERPRETATION. Categorical Data Analysis and Misclassification (J. Kuha & C. Skinner). Index.

Total survey error in practice

This book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework for understanding and improving survey data quality. The book also addresses issues with data quality in official statistics and in social, opinion, and market research as these fields continue to evolve, leading to larger and messier data sets. This perspective challenges survey organizations to find ways to collect and process data more efficiently without sacrificing quality. The volume consists of the most up-to-date research and reporting from over 70 contributors representing the best academics and researchers from a range of fields. The chapters are broken out into five main sections: The Concept of TSE and the TSE Paradigm, Implications for Survey Design, Data Collection and Data Processing Applications, Evaluation and Improvement, and Estimation and Analysis. Each chapter introduces and examines multiple error sources, such as sampling error, measurement error, and nonresponse error, which often offer the greatest risks to data quality, while also encouraging readers not to lose sight of the less commonly studied error sources, such as coverage error, processing error, and specification error. The book also notes the relationships between errors and the ways in which efforts to reduce one type can increase another, resulting in an estimate with larger total error.

Measurement Errors in Surveys

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.