Enhanced descriptions from Syndetics:

An accessible introduction to the science and application of sample surveys
Over the past two decades, survey research has evolved significantly. Survey Methodology describes the basic principles of survey design discovered in methodological research over recent years and offers guidance for making successful decisions in the design and execution of high quality surveys. Written by six nationally recognized experts in the field, this book covers the major considerations in designing and conducting a sample survey. Topical, accessible, and succinct, this book represents the state of the science in survey methodology. Employing the "total survey error" paradigm as an organizing framework, it merges the science of surveys with state-of-the-art practices. End-of-chapter terms, references, and exercises enhance its value as a reference for practitioners and as a text for advanced students.

Table of contents provided by Syndetics

• Preface (p. xv)
• Acknowledgements (p. xix)
• Chapter 1. An Introduction to Survey Methodology
• 1.1 Introduction (p. 2)
• 1.2 A Brief History of Survey Research (p. 3)
• 1.2.1 The Purposes of Surveys (p. 3)
• 1.2.2 The Development of Standardized Questioning (p. 5)
• 1.2.3 The Development of Sampling Methods (p. 6)
• 1.2.4 The Development of Data Collection Methods (p. 7)
• 1.3 Some Examples of Ongoing Surveys (p. 7)
• 1.3.1 The National Crime Victimization Survey (p. 8)
• 1.3.2 The National Survey on Drug Use and Health (p. 13)
• 1.3.3 The Survey of Consumers (p. 17)
• 1.3.4 The National Assessment of Educational Progress (p. 20)
• 1.3.5 The Behavioral Risk Factor Surveillance System (p. 24)
• 1.3.6 The Current Employment Statistics Program (p. 27)
• 1.3.7 What Can We Learn From the Six Example Surveys? (p. 29)
• 1.4 What is Survey Methodology? (p. 30)
• 1.5 The Challenge of Survey Methodology (p. 32)
• 1.6 About this Book (p. 34)
• Chapter 2. Inference and Error in Surveys
• 2.1 Introduction (p. 39)
• 2.2 The Lifecycle of a Survey From a Design Perspective (p. 41)
• 2.2.1 Constructs (p. 41)
• 2.2.2 Measurement (p. 43)
• 2.2.3 Response (p. 43)
• 2.2.4 Edited Response (p. 44)
• 2.2.5 The Target Population (p. 44)
• 2.2.6 The Frame Population (p. 45)
• 2.2.7 The Sample (p. 45)
• 2.2.8 The Respondents (p. 45)
• 2.2.9 Postsurvey Adjustments (p. 46)
• 2.2.10 How Design Becomes Process (p. 47)
• 2.3 The Lifecycle of a Survey from A Quality Perspective (p. 49)
• 2.3.1 The Observational Gap between Constructs and Measures (p. 50)
• 2.3.2 Measurement Error: The Observational Gap between the Ideal Measurement and the Response Obtained (p. 51)
• 2.3.3 Processing Error: the Observational Gap between the Variable Used in Estimation and that Provided by the Respondent (p. 53)
• 2.3.4 Coverage Error: the Nonobservational Gap between the Target Population and the Sampling Frame (p. 54)
• 2.3.5 Sampling Error: The Nonobservational Gap between the Sample and the Sampling Frame (p. 57)
• 2.3.6 Nonresponse Error: The Nonobservational Gap between the Sampling and the Respondent Pool (p. 58)
• 2.3.7 Adjustment Error (p. 59)
• 2.4 Putting It All Together (p. 60)
• 2.5 Error Notions in Different Kinds of Statistics (p. 61)
• 2.6 Summary (p. 62)
• Chapter 3. Target Populations, Sampling Frames, and Coverage Error
• 3.1 Introduction (p. 67)
• 3.2 Populations and Frames (p. 67)
• 3.3 Coverage Properties of Sampling Frames (p. 70)
• 3.3.1 Undercoverage (p. 70)
• 3.3.2 Ineligible Units (p. 74)
• 3.3.3 Clustering of Target Population Elements Within Frame Elements (p. 75)
• 3.3.4 Duplication of Target Population Elements in Sampling Frames (p. 77)
• 3.3.5 Complicated Mappings between Frame and Target Population Elements (p. 78)
• 3.4 Common Target Populations and Their Frame Issues (p. 79)
• 3.4.1 Households and Persons (p. 79)
• 3.4.2 Customers, Employees, or Members of an Organization (p. 80)
• 3.4.3 Organizations (p. 81)
• 3.4.4 Events (p. 82)
• 3.4.5 Rare Populations (p. 83)
• 3.5 Coverage Error (p. 83)
• 3.6 Reducing Undercoverage (p. 84)
• 3.6.1 The Half-Open Interval (p. 84)
• 3.6.2 Multiplicity Sampling (p. 86)
• 3.6.3 Multiple Frame Designs (p. 87)
• 3.6.4 Increasing Coverage While Including More Ineligible Elements (p. 90)
• 3.7 Summary (p. 90)
• Chapter 4. Sample Design and Sampling Error
• 4.1 Introduction (p. 93)
• 4.2 Samples and Estimates (p. 95)
• 4.3 Simple Random Sampling (p. 99)
• 4.4 Cluster Sampling (p. 102)
• 4.4.1 The Design Effect and Within-Cluster Homogeneity (p. 105)
• 4.4.2 Subsampling within Selected Clusters (p. 108)
• 4.5 Stratification and Stratified Sampling (p. 109)
• 4.5.1 Proportionate Allocation to Strata (p. 111)
• 4.5.2 Disproportionate Allocation to Strata (p. 117)
• 4.6 Systematic Selection (p. 118)
• 4.7 Complications in Practice (p. 121)
• 4.7.1 Two-Stage Cluster Designs with Probabilities Proportionate to Size (PPS) (p. 122)
• 4.7.2 Multistage and Other Complex Designs (p. 124)
• 4.7.3 How Complex Sample Designs are Described: The Sample Design for the NCVS (p. 125)
• 4.8 Sampling Persons in US Telephone Households (p. 128)
• 4.9 Summary (p. 130)
• Chapter 5. Methods of Data Collection
• 5.1 Alternative Methods of Data Collection (p. 138)
• 5.1.1 Degree of Interviewer Involvement (p. 141)
• 5.1.2 Degree of Interaction with the Respondent (p. 142)
• 5.1.3 Degree of Privacy (p. 142)
• 5.1.4 Channels of Communication (p. 143)
• 5.1.5 Technology Use (p. 145)
• 5.1.6 Implications of these Dimensions (p. 145)
• 5.2 Choosing the Appropriate Method (p. 146)
• 5.3 Effects of Different Data Collection Methods on Survey Errors (p. 147)
• 5.3.1 Measuring the Marginal Effect of Mode (p. 148)
• 5.3.2 Sampling Frame and Sample Design Implications of Mode Selection (p. 150)
• 5.3.3 Coverage Implications of Mode Selection (p. 150)
• 5.3.4 Nonresponse Implications of Mode Selection (p. 153)
• 5.3.5 Measurement Quality Implications of Mode Selection (p. 155)
• 5.3.6 Cost Implications (p. 160)
• 5.3.7 Summary on the Choice of Method (p. 162)
• 5.4 Using Multiple Modes of Data Collection (p. 163)
• 5.5 Summary (p. 165)
• Chapter 6. Nonresponse in Sample Surveys
• 6.1 Introduction (p. 169)
• 6.2 Three Major Types of Unit Nonresponse (p. 169)
• 6.2.1 Unit Nonresponse Due to Failure to Deliver the Survey Request (p. 170)
• 6.2.2 Unit Nonresponse Due to Refusals (p. 173)
• 6.2.3 Unit Nonresponse Due to the Inability to Provide the Requested Data (p. 178)
• 6.3 How Does Nonresponse Affect the Quality of Survey Statistics? (p. 178)
• 6.4 Computing Response and Nonresponse Rates (p. 181)
• 6.5 Trends in Response Rates over Time (p. 184)
• 6.6 Item Nonresponse (p. 187)
• 6.7 Design Features to Reduce Unit Nonresponse (p. 189)
• 6.8 Summary (p. 195)
• Chapter 7. Questions and Answers in Surveys
• 7.1 Alternatives Methods of Survey Measurement (p. 201)
• 7.2 Cognitive Processes in Answering Questions (p. 202)
• 7.2.1 Comprehension (p. 204)
• 7.2.2 Retrieval (p. 205)
• 7.2.3 Estimation and Judgment (p. 206)
• 7.2.4 Reporting (p. 207)
• 7.2.5 Other Models of the Response Process (p. 207)
• 7.3 Problems in Answering Survey Questions (p. 209)
• 7.3.1 Encoding Problems (p. 209)
• 7.3.2 Misinterpreting the Questions (p. 210)
• 7.3.3 Forgetting and Other Memory Problems (p. 213)
• 7.3.4 Estimation Processes for Behavioral Questions (p. 218)
• 7.3.5 Judgment Processes for Attitude Questions (p. 220)
• 7.3.6 Formatting the Answer (p. 221)
• 7.3.7 Motivated Misreporting (p. 224)
• 7.3.8 Navigational Errors (p. 225)
• 7.4 Guidelines for Writing Good Questions (p. 226)
• 7.4.1 Nonsensitive Questions About Behavior (p. 227)
• 7.4.2 Sensitive Questions About Behavior (p. 230)
• 7.4.3 Attitude Questions (p. 232)
• 7.4.4 Self-Administered Questions (p. 235)
• 7.5 Summary (p. 236)
• Chapter 8. Evaluating Survey Questions
• 8.1 Introduction (p. 241)
• 8.2 Expert Reviews (p. 242)
• 8.3 Focus Groups (p. 243)
• 8.4 Cognitive Interviews (p. 245)
• 8.5 Field Pretests and Behavior Coding (p. 247)
• 8.6 Randomized or Split-Ballot Experiments (p. 249)
• 8.7 Applying Question Standards (p. 250)
• 8.8 Summary of Question Evaluation Tools (p. 251)
• 8.9 Linking Concepts of Measurement Quality to Statistical Estimates (p. 254)
• 8.9.1 Validity (p. 254)
• 8.9.2 Response Bias (p. 258)
• 8.9.3 Reliability and Simple Response Variance (p. 261)
• 8.10 Summary (p. 265)
• Chapter 9. Survey Interviewing
• 9.1 The Role of the Interviewer (p. 269)
• 9.2 Interviewer Bias (p. 270)
• 9.2.1 Systematic Interviewer Effects on Reporting of Socially Undesirable Attributes (p. 270)
• 9.2.2 Systematic Interviewer Effects on Topics Related to Observable Interviewer Traits (p. 270)
• 9.2.3 Systematic Interviewer Effects Associated with Interviewer Experience (p. 272)
• 9.3 Interviewer Variance (p. 274)
• 9.3.1 Randomization Requirements for Estimating Interviewer Variance (p. 274)
• 9.3.2 Estimation of Interviewer Variance (p. 275)
• 9.4 Strategies for Reducing Interviewer Bias (p. 278)
• 9.4.1 The Role of the Interviewer in Motivating Respondent Behavior (p. 278)
• 9.4.2 Changing Interviewer Behavior (p. 279)
• 9.5 Strategies for Reducing Interviewer-Related Variance (p. 280)
• 9.5.1 Minimizing Questions that Require Nonstandard Interviewer Behavior (p. 281)
• 9.5.2 Professional, Task-Oriented Interviewer Behavior (p. 283)
• 9.5.3 Interviewers Reading Questions as They Are Worded (p. 284)
• 9.5.4 Interviewers Explaining the Survey Process to the Respondent (p. 284)
• 9.5.5 Interviewers Probing Nondirectively (p. 286)
• 9.5.6 Interviewers Recording Answers Exactly as Given (p. 289)
• 9.5.7 Summary on Strategies to Reduce Interviewer Variance (p. 290)
• 9.6 The Controversy About Standardized Interviewing (p. 290)
• 9.7 Interviewer Management (p. 293)
• 9.7.1 Interviewer Selection (p. 293)
• 9.7.2 Interviewer Training (p. 294)
• 9.7.3 Interviewer Supervision and Monitoring (p. 295)
• 9.7.4 The Size of Interviewer Workloads (p. 296)
• 9.7.5 Interviewers and Computer Use (p. 296)
• 9.8 Summary (p. 297)
• Chapter 10. Postcollection Processing of Survey Data
• 10.1 Introduction (p. 303)
• 10.2 Coding (p. 305)
• 10.2.1 Practical Issues of Coding (p. 306)
• 10.2.2 Theoretical Issues in Coding Activities (p. 308)
• 10.2.3 "Field Coding"--An Intermediate Design (p. 308)
• 10.2.4 Standard Classification Systems (p. 311)
• 10.2.5 Other Common Coding Systems (p. 315)
• 10.2.6 Quality Indicators in Coding (p. 316)
• 10.2.7 Summary of Coding (p. 318)
• 10.3 Entering Numeric Data into Files (p. 318)
• 10.4 Editing (p. 319)
• 10.5 Weighting (p. 321)
• 10.5.1 Weighting with a First-Stage Ratio Adjustment (p. 322)
• 10.5.2 Weighting for Differential Selection Probabilities (p. 323)
• 10.5.3 Weighting to Adjust for Unit Nonresponse (p. 324)
• 10.5.4 Poststratification Weighting (p. 326)
• 10.5.5 Putting All the Weights Together (p. 326)
• 10.6 Imputation for Item-missing data (p. 329)
• 10.7 Sampling Variance Estimation for Complex Samples (p. 333)
• 10.8 Survey Data Documentation and Metadata (p. 337)
• 10.9 Summary of Postsurvey Processing (p. 340)
• Chapter 11. Principles and Practices Related to Scientific Integrity
• 11.1 Introduction (p. 345)
• 11.2 Standards for the Conduct of Research (p. 345)
• 11.3 Standards for Dealing with Clients (p. 348)
• 11.4 Standards for Dealing with the Public (p. 349)
• 11.5 Standards for Dealing with Respondents (p. 350)
• 11.5.1 Legal Obligations to Survey Respondents (p. 350)
• 11.5.2 Ethical Obligations to Respondents (p. 351)
• 11.5.3 Informed Consent: Respect for Persons (p. 353)
• 11.5.4 Beneficence: Protecting Respondents from Harm (p. 355)
• 11.5.5 Efforts at Persuasion (p. 357)
• 11.6 Emerging Ethical Issues (p. 358)
• 11.7 Practices in Research Administration Regarding Human Subject Issues (p. 358)
• 11.8 Research About Informed Consent Protocols in Surveys (p. 360)
• 11.8.1 Research on Respondents' Reactions to the Content of Informed Consent Protocols (p. 360)
• 11.8.2 Research on Informed Consent Complications in Survey Methodological Studies (p. 364)
• 11.8.3 Research on Written versus Oral Informed Consent (p. 365)
• 11.8.4 Summary of Research on Informed Consent in Surveys (p. 366)
• 11.9 Procedures to Detect and Repair Interviewer Falsification (p. 366)
• 11.10 Disclosure Limitation Procedures (p. 368)
• 11.10.1 Administrative Procedures to Limit Identifiability of Survey Materials (p. 368)
• 11.10.2 Restricting Access to the Data Only to Those Subscribing to a Pledge of Confidentiality (p. 368)
• 11.10.3 Restricting the Contents of the Survey Data That May Be Released (p. 370)
• 11.11 Summary and Conclusions (p. 372)
• Chapter 12. FAQs about Survey Methodology
• 12.1 Introduction (p. 377)
• 12.2 The Questions and Their Answers (p. 377)
• References (p. 391)
• Index (p. 415)

Author notes provided by Syndetics

Robert M. Groves is Research Professor and Director at the University of Michigan Survey Research Center, Professor of Sociology at the University of Michigan, and a Research Professor at the Joint Program in Survey Methodology at the University of Maryland
Floyd J. Fowler, Jr., is President of the Foundation for Informed Medical Decision-Making and a Senior Research Fellow at the Center for Survey Research, University of Massachusetts, Boston
Mick P. Couper is a Research Associate Professor at the University of Michigan Survey Research Center and at the Joint Program in Survey Methodology at the University of Maryland
James M. Lepkowski is Research Professor at the University of Michigan Survey Research Center, Associate Professor of Biostatistics, Director of the Graduate Program in Survey Methodology, University of Michigan, and a Research Professor at the Joint Program in Survey Methodology at the University of Maryland
Eleanor Singer is a Research Professor at the University of Michigan Survey Research Center, and an Adjunct Professor of Sociology at the University of Michigan
Roger Tourangeau is Research Professor at the University of Michigan Survey Research Center and Director of the Joint Program in Survey Methodology at the University of Maryland