
Applied Survey Methods A Statistical Perspective
by Bethlehem, Jelke-
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Summary
Author Biography
Jelke Bethlehem, PhD, is Senior Advisor in the Department of Statistical Methods at Statistics Netherlands and Professor of Statistical Information Processing at the University of Amsterdam. Dr. Bethlehem's current research interests include Web surveys, computer-assisted survey information collection, graphical techniques in statistics, and user-friendly software for statistical analysis. He is coeditor of Computer Assisted Survey Information Collection, also published by Wiley.
Table of Contents
Preface | p. ix |
The Survey Process | p. 1 |
About Surveys | p. 1 |
A Survey, Step-by-Step | p. 2 |
Some History of Survey Research | p. 4 |
This Book | p. 10 |
Samplonia | p. 11 |
Exercises | p. 13 |
Basic Concepts | p. 15 |
The Survey Objectives | p. 15 |
The Target Population | p. 16 |
The Sampling Frame | p. 20 |
Sampling | p. 22 |
Estimation | p. 33 |
Exercises | p. 41 |
Questionnaire Design | p. 43 |
The Questionnaire | p. 43 |
Factual and Nonfactual Questions | p. 44 |
The Question Text | p. 45 |
Answer Types | p. 50 |
Question Order | p. 55 |
Questionnaire Testing | p. 58 |
Exercises | p. 63 |
Single Sampling Designs | p. 65 |
Simple Random Sampling | p. 65 |
Systematic Sampling | p. 75 |
Unequal Probability Sampling | p. 82 |
Systematic Sampling with Unequal Probabilities | p. 89 |
Exercises | p. 96 |
Composite Sampling Designs | p. 100 |
Stratified Sampling | p. 100 |
Cluster Sampling | p. 108 |
Two-Stage Sampling | p. 113 |
Two-Dimensional Sampling | p. 122 |
Exercises | p. 130 |
Estimators | p. 134 |
Use of Auxiliary Information | p. 134 |
A Descriptive Model | p. 134 |
The Direct Estimator | p. 137 |
The Ratio Estimator | p. 139 |
The Regression Estimator | p. 143 |
The Poststratification Estimator | p. 146 |
Exercises | p. 149 |
Data Collection | p. 153 |
Traditional Data Collection | p. 153 |
Computer-Assisted Interviewing | p. 155 |
Mixed-Mode Data Collection | p. 160 |
Electronic Questionnaires | p. 163 |
Data Collection with Blaise | p. 167 |
Exercises | p. 176 |
The Quality of the Results | p. 178 |
Errors in Surveys | p. 178 |
Detection and Correction of Errors | p. 181 |
Imputation Techniques | p. 185 |
Data Editing Strategies | p. 195 |
Exercises | p. 206 |
The Nonresponse Problem | p. 209 |
Nonresponse | p. 209 |
Response Rates | p. 212 |
Models for Nonresponse | p. 218 |
Analysis of Nonresponse | p. 225 |
Nonresponse Correction Techniques | p. 236 |
Exercises | p. 245 |
Weighting Adjustment | p. 249 |
Introduction | p. 249 |
Poststratification | p. 250 |
Linear Weighting | p. 253 |
Multiplicative Weighting | p. 260 |
Calibration Estimation | p. 263 |
Other Weighting Issues | p. 264 |
Use of Propensity Scores | p. 266 |
A Practical Example | p. 268 |
Exercises | p. 272 |
Online Surveys | p. 276 |
The Popularity of Online Research | p. 276 |
Errors in Online Surveys | p. 277 |
The Theoretical Framework | p. 283 |
Correction by Adjustment Weighting | p. 288 |
Correction Using a Reference Survey | p. 293 |
Sampling the Non-Internet Population | p. 296 |
Propensity Weighting | p. 297 |
Simulating the Effects of Undercoverage | p. 299 |
Simulating the Effects of Self-Selection | p. 301 |
About the Use of Online Surveys | p. 305 |
Exercises | p. 307 |
Analysis and Publication | p. 310 |
About Data Analysis | p. 310 |
The Analysis of Dirty Data | p. 312 |
Preparing a Survey Report | p. 317 |
Use of Graphs | p. 322 |
Exercises | p. 339 |
Statistical Disclosure Control | p. 342 |
Introduction | p. 342 |
The Basic Disclosure Problem | p. 343 |
The Concept of Uniqueness | p. 344 |
Disclosure Scenarios | p. 347 |
Models for the Disclosure Risk | p. 349 |
Practical Disclosure Protection | p. 353 |
Exercises | p. 356 |
References | p. 359 |
Index | p. 369 |
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