Survey Methodology 2nd Edition by Robert M. Groves, ISBN-13: 978-0470465462

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Survey Methodology 2nd Edition by Robert M. Groves, ISBN-13: 978-0470465462

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• Publisher: ‎ Wiley; 2nd edition (June 29, 2009)
• Language: ‎ English
• ISBN-10: ‎ 0470465468
• ISBN-13: ‎ 978-0470465462

This new edition of Survey Methodology continues to provide a state-of-the-science presentation of essential survey methodology topics and techniques. The volume’s six world-renowned authors have updated this Second Edition to present newly emerging approaches to survey research and provide more comprehensive coverage of the major considerations in designing and conducting a sample survey.

Key topics in survey methodology are clearly explained in the book’s chapters, with coverage including sampling frame evaluation, sample design, development of questionnaires, evaluation of questions, alternative modes of data collection, interviewing, nonresponse, post-collection processing of survey data, and practices for maintaining scientific integrity. Acknowledging the growing advances in research and technology, the Second Edition features:

• Updated explanations of sampling frame issues for mobile telephone and web surveys
• New scientific insight on the relationship between nonresponse rates and nonresponse errors
• Restructured discussion of ethical issues in survey research, emphasizing the growing research results on privacy, informed consent, and confidentiality issues
• The latest research findings on effective questionnaire development techniques
• The addition of 50% more exercises at the end of each chapter, illustrating basic principles of survey design
• An expanded FAQ chapter that addresses the concerns that accompany newly established methods

Providing valuable and informative perspectives on the most modern methods in the field, Survey Methodology, Second Edition is an ideal book for survey research courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing survey methodologists and any professional who employs survey research methods.

Table of Contents:

Front Matter

PREFACE TO THE FIRST EDITION

PREFACE TO THE SECOND EDITION

ACKNOWLEDGMENTS

CHAPTER ONE AN INTRODUCTION TO SURVEY METHODOLOGY

A Note to the Reader

1.1 Introduction

1.2 A Brief History of Survey Research

1.2.1 The Purposes of Surveys

Schuman (1997) on “Poll” Versus “Survey”

1.2.2 The Development of Standardized Questioning

1.2.3 The Development of Sampling Methods

1.2.4 The Development of Data Collection Methods

1.3 Some Examples of Ongoing Surveys

1.3.1 The National Crime Victimization Survey

Table 1.1. Example Survey: National Crime Victimization Survey (NCVS)

Figure 1.1 Percentage of U.S. households experiencing a crime by type, 1994-2005 National Crime Victimization Survey.

1.3.2 The National Survey on Drug Use and Health

Table 1.2. Example Survey: National Survey of Drug Use and Health (NSDUH)

Figure 1.2 Percentage of persons reporting illicit drug use in past month, by drug type, 2004-2006

1.3.3 The Surveys of Consumers

Table 1.3. Example Survey: Surveys of Consumers (SOC)

Figure 1.3 Consumer unemployment expectations and actual change in the U.S. unemployment rate, 1969-2009

1.3.4 The National Assessment of Educational Progress

Table 1.4. Example Survey: National Assessment of Educational Progress (NAEP)

Figure 1.4 Average scale scores on grade 12 mathematics assessment, by year by type of school.

1.3.5 The Behavioral Risk Factor Surveillance System

Table 1.5. Example Survey: Behavioral Risk Factor Surveillance System (BRFSS)

Figure 1.5a Percentage of state adults who are obese (body mass index ≥ 30) by state, 1994, BRFSS.

Figure 1.5b Percentage of state adults who are obese (body mass index ≥ 30) by state, 2001, BRFSS.

Figure 1.5c Percentage of state adults who are obese (body mass index ≥ 30) by state, 2007, BRFSS.

1.3.6 The Current Employment Statistics Program

Table 1.6. Example Survey: Current Employment Statistics (CES)

Figure 1.6 Number of employees of all nonfarm employers in thousands, annual estimates 1947-2007, Current Employment Statistics.

1.3.7 What Can We Learn From the Six Example Surveys?

1.4 What is Survey Methodology?

1.5 The Challenge of Survey Methodology

1.6 About this Book

Keywords

For More In-Depth Reading

National Crime Victimization Survey

National Survey of Drug Use and Health

Surveys of Consumers

National Assessment of Educational Progress

Behavioral Risk Factor Surveillance System

Current Employment Statistics

Exercises

CHAPTER TWO INFERENCE AND ERROR IN SURVEYS

2.1 Introduction

Figure 2.1 Two types of survey inference.

2.2 The Life Cycle of a Survey From a Design Perspective

Figure 2.2 Survey lifecycle from a design perspective.

2.2.1 Constructs

2.2.2 Measurement

2.2.3 Response

2.2.4 Edited Response

2.2.5 The Target Population

2.2.6 The Frame Population

Illustration—Populations of Inference and Target Populations

2.2.7 The Sample

2.2.8 The Respondents

Figure 2.3 Unit and item nonresponse in a survey data file.

2.2.9 Postsurvey Adjustments

2.2.10 How Design Becomes Process

Figure 2.4 A survey from a process perspective.

2.3 The Life Cycle of a Survey from A Quality Perspective

Figure 2.5 Survey life cycle from a quality perspective.

2.3.1 The Observational Gap between Constructs and Measures

The Notion of Trials

2.3.2 Measurement Error: The Observational Gap between the Ideal Measurement and the Response Obtained

The Notion of Variance or Variable Errors

2.3.3 Processing Error: The Observational Gap between the Variable Used in Estimation and that Provided by the Respondent

2.3.4 Coverage Error: The Nonobservational Gap between the Target Population and the Sampling Frame

Figure 2.6 Coverage of a target population by a frame.

2.3.5 Sampling Error: The Nonobservational Gap between the Sampling Frame and the Sample

Figure 2.7 Samples and the sampling distribution of the mean.

2.3.6 Nonresponse Error: The Nonobservational Gap between the Sample and the Respondent Pool

2.3.7 Adjustment Error

2.4 Putting It All Together

2.5 Error Notions in Different Kinds of Statistics

2.6 Nonstatistical Notions of Survey Quality

2.7 Summary

Keywords

For More In-Depth Reading

Exercises

CHAPTER THREE TARGET POPULATIONS, SAMPLING FRAMES, AND COVERAGE ERROR

3.1 Introduction

3.2 Populations and Frames

3.3 Coverage Properties of Sampling Frames

3.3.1 Undercoverage

Mulry (2007) on U.S. Decennial Census Coverage

3.3.2 Ineligible Units

3.3.3 Clustering of Target Population Elements Within Frame Elements

Figure 3.1 Cluster of target population elements associated with one sampling frame element.

3.3.4 Duplication of Target Population Elements in Sampling Frames

Figure 3.2 Duplication of target population elements by more than one sampling frame element.

3.3.5 Complicated Mappings between Frame and Target Population Elements

Figure 3.3 Clustering and duplication of target population elements relative to sampling frame elements.

3.4 Alternative Frames for Surveys of the Target Population of Households or Persons

3.4.1 Area Frames

3.4.2 Telephone Number Frames for Households and Persons

Figure 3.4 Percentage of U.S. adults with wireless telephone service only and percentage without telephones, January, 2004-June, 2008.

3.4.3 Frames for Web Surveys of General Populations

3.5 Frame Issues for Other Common Target Populations

3.5.1 Customers, Employees, or Members of an Organization

3.5.2 Organizations

3.5.3 Events

3.5.4 Rare Populations

3.6 Coverage Error

3.7 Reducing Undercoverage

3.7.1 The Half-Open Interval

Figure 3.5 Address list for area household survey block.

Figure 3.6 Sketch map for area household survey block.

3.7.2 Multiplicity Sampling

3.7.3 Multiple Frame Designs

Figure 3.7 Dual frame sample design.

3.7.4 Increasing Coverage While Including More Ineligible Elements

Tourangeau, Shapiro, Kearney, and Ernst (1997) and Martin (1999) on Household Rosters

3.8 Summary

Keywords

For More in-Depth Reading

Exercises

CHAPTER FOUR SAMPLE DESIGN AND SAMPLING ERROR

4.1 Introduction

4.2 Samples and Estimates

Figure 4.1 Unknown distribution for variable Y in frame population.

Figure 4.2 Distributions of y variable from sample realizations samples and the sampling distribution of the mean.

Figure 4.3 Key notation for sample realization, frame population, and sampling distribution of sample means.

Warning

4.3 Simple Random Sampling

Comment

Comment

4.4 Cluster Sampling

Figure 4.4 A bird’s-eye view of a population of 30 “” and 30 “” households clustered into six city blocks, from which two blocks are selected.

Comment

4.4.1 The Design Effect and Within-Cluster Homogeneity

Table 4.1. Mean roh Values for Area Probability Surveys about Female Fertility Experiences in Five Countries by Type of Variable

Kish and Frankel (1974) on Design Effects for Regression Coefficients

4.4.2 Subsampling within Selected Clusters

4.5 Stratification and Stratified Sampling

Figure 4.5 Frame population of 20 establishments sorted alphabetically, with SRS sample realization of size n = 4.

Figure 4.6 Frame population of 20 establishments sorted by group, with stratified element sample of size nh = 1 from each stratum.

4.5.1 Proportionate Allocation to Strata

Table 4.2. Proportionate Stratified Random Sample Results from a School Population Divided Into Three Urbanicity Strata

Cochran (1961) on How Many Strata to Use

Design Effects for the Stratified Mean

4.5.2 Disproportionate Allocation to Strata

Neyman (1934) on Stratified Random Sampling

4.6 Systematic Selection

Figure 4.7 Frame population of 20 establishments sorted by group with systematic selection; selection interval = 5 and random start = 2.

Comment

4.7 Complications in Practice

4.7.1 Two-Stage Cluster Designs with Probabilities Proportionate to Size (PPS)

Table 4.3. Block Housing Unit Counts and Cumulative Counts for a Population of Nine Blocks

4.7.2 Multistage and Other Complex Designs

4.7.3 How Complex Sample Designs Are Described: The Sample Design for the NCVS

4.8 Sampling U.S. Telephone Households

Figure 4.8 Number of 100 blocks of number by number listed within the block, 1986 and 2008. (Source: Survey Sampling, Inc.)

4.9 Selecting Persons within Households

4.10 Summary

Keywords

For More In-Depth Reading

Exercises

CHAPTER FIVE METHODS OF DATA COLLECTION

Figure 5.1 A survey from a process perspective.

5.1 Alternative Methods of Data Collection

Figure 5.2 The evolution of survey technology.

5.1.1 Degree of Interviewer Involvement

5.1.2 Degree of Interaction with the Respondent

5.1.3 Degree of Privacy

5.1.4 Channels of Communication

5.1.5 Technology Use

5.1.6 Implications of these Dimensions

5.2 Choosing the Appropriate Method

5.3 Effects of Different Data Collection Methods on Survey Errors

5.3.1 Measuring the Marginal Effect of Mode

Table 5.1. Design Issues in Research Comparing Face-to-Face and Telephone Surveys

Hochstim (1967) on Personal Interviews Versus Telephone Interviews Versus Mail Questionnaires

The de Leeuw and van der Zouwen (1998) Meta-Analysis of Data Quality in Telephone and Face-to-Face Surveys

5.3.2 Sampling Frame and Sample Design Implications of Mode Selection

5.3.3 Coverage Implications of Mode Selection

Figure 5.3 Percentage of U.S. adults who ever use the Internet, quarter 1, 2000, to quarter 3, 2008.

5.3.4 Nonresponse Implications of Mode Selection

5.3.5 Measurement Quality Implications of Mode Selection

The Tourangeau and Smith (1996) Study of Mode Effects on Answers to Sensitive Questions

Figure 5.4 Ratio of proportion of respondents reporting illicit drug use in self-administered versus interviewer-administered questionnaires, by time period by drug.

5.3.6 Cost Implications

5.3.7 Summary on the Choice of Method

5.4 Using Multiple Modes of Data Collection

Figure 5.5 Five different types of mixed mode designs.

5.5 Summary

Keywords

For More In-Depth Reading

Exercises

CHAPTER SIX NONRESPONSE IN SAMPLE SURVEYS

6.1 Introduction

6.2 Response Rates

6.2.1 Computing Response Rates

Merkle and Edelman (2002) on How Nonresponse Rates Affect Nonresponse Error

6.2.2 Trends in Response Rates Over Time

Figure 6.1 Household nonresponse rate, household refusal rate, and person refusal rate for the National Crime Victimization Survey by year.

Figure 6.2 Nonresponse and refusal rates for the Current Population Survey by year.

Figure 6.3 Nonresponse rate and refusal rate for the Survey of Consumers by year.

Figure 6.4 Median nonresponse rate across states, Behavioral Risk Factor Surveillance System, 1987-2007.

6.3 Impact of Nonresponse on the Quality of Survey Estimates

Figure 6.5 Estimates of the absolute value of the relative nonresponse bias for 959 estimates by nonresponse rate of survey.

6.4 Thinking Causally About Survey Nonresponse Error

Figure 6.6 Alternative models for relationship between response propensity (P) and survey variable (Y), involving auxiliary variables (S, Z).

6.5 Dissecting The Nonresponse Phenomenon

6.5.1 Unit Nonresponse Due to Failure to Deliver the Survey Request

Figure 6.7 Causal influences on contact with sample household.

Figure 6.8 Percentage of eligible sample households by calls to first contact for five surveys.

Figure 6.9 Percentage household contacted among those previously uncontacted by call number by time of day. (National Survey of Family Growth, Cycle 6.)

Figure 6.10 Percentage nonresponse bias for estimated proportion of single person households, by number of calls required to reach the house hold, for four surveys.

6.5.2 Unit Nonresponse Due to Refusals

The “I’m Not Selling Anything” Phenomenon

Figure 6.11 Two sample persons with different leverages for attributes of a survey request.

What Interviewers Say

6.5.3 Unit Nonresponse Due to the Inability to Provide the Requested Data

6.6 Design Features to Reduce Unit Nonresponse

Figure 6.12 Tools for reducing unit nonresponse rates.

What Interviewers Say about Approaching Sample Households

Berlin, Mohadjer. Waksberg, Kolstad, Kirsch, Rock, and Yamamoto (1992) on Incentives and Interviewer Productivity

Morton-Williams (1993) on Tailoring Behavior by Interviewers

6.7 Item Nonresponse

Figure 6.13 Beatty-Herrmann model of response process for item-missing data.

6.8 Are Nonresponse Propensities Related To Other Error Sources?

6.9 Summary

Keywords

For More In-Depth Reading

Exercises

CHAPTER SEVEN QUESTIONS AND ANSWERS IN SURVEYS

7.1 Alternatives Methods of Survey Measurement

7.2 Cognitive Processes in Answering Questions

Figure 7.1 A simple model of the survey response process.

7.2.1 Comprehension

7.2.2 Retrieval

7.2.3 Estimation and Judgment

7.2.4 Reporting

7.2.5 Other Models of the Response Process

Comments on Response Strategies

7.3 Problems in Answering Survey Questions

7.3.1 Encoding Problems

Fowler (1992) on Unclear Terms in Questions

7.3.2 Misinterpreting the Questions

7.3.3 Forgetting and Other Memory Problems

Figure 7.2 Recall accuracy for types of personal information.

Table 7.1. Summary of Factors Affecting Recall

Neter and Waksberg (1964) on Response Errors

7.3.4 Estimation Processes for Behavioral Questions

Overreporting and Underreporting

Schwarz, Hippler, Deutsch, and Strack (1985) on Response Scale Effects

7.3.5 Judgment Processes for Attitude Questions

7.3.6 Formatting the Answer

7.3.7 Motivated Misreporting

7.3.8 Navigational Errors

Figure 7.3 Example questions from Jenkins and Dillman (1997).

7.4 Guidelines for Writing Good Questions

7.4.1 Nonsensitive Questions About Behavior

7.4.2 Sensitive Questions About Behavior

7.4.3 Attitude Questions

7.4.4 Self-Administered Questions

Figure 7.4 Illustration of use of visual contrast to highlight the response box.

7.5 Summary

Keywords

For More In-Depth Reading

Exercises

CHAPTER EIGHT EVALUATING SURVEY QUESTIONS

8.1 Introduction

8.2 Expert Reviews

8.3 Focus Groups

8.4 Cognitive Interviews

Presser and Blair (1994) on Alternative Pretesting Methods

8.5 Field Pretests and Behavior Coding

Table 8.1. Examples of Behavior Codes for Interviewer and Respondent Behaviors

8.6 Randomized or Split-Ballot Experiments

Oksenberg, Cannell, and Kalton (1991) on Probes and Behavior Coding

Percent of problems per question

8.7 Applying Question Standards

8.8 Summary of Question Evaluation Tools

Table 8.2. Studies Comparing Question Evaluation Methods

8.9 Linking Concepts of Measurement Quality to Statistical Estimates

8.9.1 Validity

Estimating Validity with Data External to the Survey.

Estimating Validity with Multiple Indicators of the Same Construct.

Figure 8.1 Path diagram representing Yαi = λαμi + ɛαi, a measurement model for μi.

8.9.2 Response Bias

Using Data on Individual Target Population Elements.

Table 8.3. Percentage of Known Hospitalizations Not Reported, by Length of Stay and Time Since Discharge

Using Population Statistics Not Subject to Survey Response Error.

8.9.3 Reliability and Simple Response Variance

Repeated Interviews with the Same Respondent.

Table 8.4. Indexes of Inconsistency for Various VictimizationIncident Characteristics, NCVS

Using Multiple Indicators of the Same Construct.

Table 8.5. Illustrative Intercorrelations among MHI-5 Items

O’Muircheartaigh (1991) on Reinterviews to Estimate Simple Response Variance

8.10 Summary

Keywords

For More In-Depth Reading

Exercises

CHAPTER NINE SURVEY INTERVIEWING

9.1 The Role of the Interviewer

9.2 Interviewer Bias

9.2.1 Systematic Interviewer Effects on Reporting of Socially Undesirable Attributes

9.2.2 Systematic Interviewer Effects on Topics Related to Observable Interviewer Traits

Schuman and Converse (1971) on Race of Interviewer Effects in the United States

Percentage Answering in Given Category by Race of Interviewer

9.2.3 Systematic Interviewer Effects Associated with Interviewer Experience

Table 9.1. Percentage Reporting Lifetime Use of Any Illicit Substance by Interview Order by Interviewer Experience (1998 NSDUH)

9.3 Interviewer Variance

9.3.1 Randomization Requirements for Estimating Interviewer Variance

9.3.2 Estimation of Interviewer Variance

Kish (1962) on Interviewer Variance

Statistics Showing High Values of ρint

9.4 Strategies for Reducing Interviewer Bias

9.4.1 The Role of the Interviewer in Motivating Respondent Behavior

9.4.2 Changing Interviewer Behavior

9.5 Strategies for Reducing Interviewer-Related Variance

9.5.1 Minimizing Questions that Require Nonstandard Interviewer Behavior

9.5.2 Professional, Task-Oriented Interviewer Behavior

9.5.3 Interviewers Reading Questions as They Are Worded

9.5.4 Interviewers Explaining the Survey Process to the Respondent

9.5.5 Interviewers Probing Nondirectively

9.5.6 Interviewers Recording Answers Exactly as Given

9.5.7 Summary on Strategies to Reduce Interviewer Variance

9.6 The Controversy About Standardized Interviewing

9.7 Interviewer Management

9.7.1 Interviewer Selection

Conrad and Schober (2000) on Standardized versus Conversational Interviewing Techniques

9.7.2 Interviewer Training

Table 9.2. Percentage of Interviewers Rated Excellent or Satisfactory for Six Criteria by Length of Interviewer Training

9.7.3 Interviewer Supervision and Monitoring

9.7.4 The Size of Interviewer Workloads

9.7.5 Interviewers and Computer Use

9.8 Validating The Work of Interviewers

Table 9.3. Percentage of Interviewers Detecting Falsifying for Three Surveys Conducted by the U.S. Bureau of the Census

9.9 The Use Of Recorded Voices (And Faces) In Data Collection

9.10 Summary

Keywords

For More In-Depth Reading

Exercises

CHAPTER TEN POSTCOLLECTION PROCESSING OF SURVEY DATA

10.1 Introduction

Figure 10.1 Flow of processing steps in paper surveys.

Figure 10.2 Flow of processing steps in computer-assisted surveys.

10.2 Coding

10.2.1 Practical Issues of Coding

10.2.2 Theoretical Issues in Coding Activities

Figure 10.3 Comprehension and judgment task of the coder.

10.2.3 “Field Coding”—An Intermediate Design

Table 10.1. Illustration of Field Coding in the NCVS for the Question “Where Did This Incident Happen?”

Collins and Courtenay (1985) on Field versus Office Coding

10.2.4 Standard Classification Systems

The Standard Occupational Classification (SOC).

Table 10.2. 23 Group Standard Occupational Classification

The North American Industry Classification System (NAICS).

Table 10.3. Comparison of SIC Divisions and NAICS Sectors

Table 10.4. NAICS Structure and Nomenclature

10.2.5 Other Common Coding Systems

10.2.6 Quality Indicators in Coding

Weaknesses in the Coding Structure.

Coder Variance.

Table 10.5. Coder Variance Statistics for Occupation Coding

10.2.7 Summary of Coding

10.3 Entering Numeric Data into Files

10.4 Editing

Summary of Editing.

10.5 Weighting

10.5.1 Weighting with a First-Stage Ratio Adjustment

10.5.2 Weighting for Differential Selection Probabilities

10.5.3 Weighting to Adjust for Unit Nonresponse

Table 10.6. Hypothetical Equal Allocation for Latinos, with Nonresponse Adjustments

10.5.4 Poststratification Weighting

Table 10.7. Weighted Sample Distribution and Poststratification for Hypothetical NCVS Sample by Gender, Age, and Ethnicity

10.5.5 Putting All the Weights Together

Ekholm and Laaksonen (1991) on Propensity Model Weighting to Adjust for Unit Nonresponse

10.6 Imputation for Item-Missing data

Figure 10.4 Unit and item nonresponse in a survey data file.

Table 10.8. Illustration of Sequential Hot-Deck Imputation for Family Income, Imputed Data, and Imputation Flag Variable

10.7 Sampling Variance Estimation for Complex Samples

Taylor Series Estimation.

Balanced Repeated Replication and Jackknife Replication.

10.8 Survey Data Documentation and Metadata

Figure 10.5 Illustration of printable codebook section for the National Crime Victimization Survey.

10.9 Summary

Keywords

For More In-Depth Reading

Exercises

CHAPTER ELEVEN PRINCIPLES AND PRACTICES RELATED TO ETHICAL RESEARCH

11.1 Introduction

11.2 Standards for the Conduct of Research

Table 11.1. Key Terminology in Research Misconduct

Table 11.2. Percentage of Interviewers Detected Falsifying for Three Surveys Conducted by the U.S. Bureau of the Census

11.3 Standards for Dealing with Clients

11.4 Standards for Dealing with the Public

Table 11.3. Elements of Minimal Disclosure (AAPOR Code)

11.5 Standards for Dealing with Respondents

11.5.1 Legal Obligations to Survey Respondents

The Tuskegee Study of Syphilis

11.5.2 Ethical Obligations to Respondents

11.5.3 Informed Consent: Respect for Persons

Table 11.4. Essential Elements of Informed Consent

Project Metropolitan

11.5.4 Beneficence: Protecting Respondents from Harm

11.5.5 Efforts at Persuasion

11.6 Emerging Ethical Issues

11.7 Research About Ethical Issues In Surveys

11.7.1 Research on Informed Consent Protocols

Research on Respondents’ Reactions to Informed Consent Protocols.

Table 11.5. Self-Reports on Type of Questions Considered Offensive to the Respondent Among Respondents Saying Researchers “Had No Business Asking” Sensitive Questions

Singer (1978) on Comprehension of Informed Consent

Research on Informed Consent Complications in Methodological Studies.

Research on Written versus Oral Informed Consent.

Summary of Research on Informed Consent in Surveys.

11.7.2 Research on Confidentiality Assurances and Survey Participation

11.8 Administrative and Technical Procedures for Safeguarding Confidentiality

11.8.1 Administrative Procedures

Figure 11.1 Pledge made by research team members about respondent privacy.

Table 11.6. Principles and Practices for Protection of Sensitive Data

11.8.2 Technical Procedures

Restricting Access to the Data.

Restricting the Contents of the Survey Data That May Be Released.

11.9 Summary and Conclusions

Keywords

For More In-Depth Reading

Exercises

CHAPTER TWELVE FAQS ABOUT SURVEY METHODOLOGY

12.1 Introduction

12.2 The Questions and Their Answers

Back Matter

REFERENCES

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