Table Of ContentQuantitative Studies in Social Relations
A p p lied
Sam pling
Seymour Sudman
A cadem ic Press, Inc.
A Subsidiary of Harcourt Brace Jovanovich, Publishers
APPLIED SAMPLING
Though many researchers working with survey
research methods are aware that powerful sam
pling techniques are available, it appears that
they avoid them because they believe these
techniques are too difficult or too costly to use.
Instead, careless ad hoc procedures are often
utilized, at times with disastrous results. AP
PLIED SAMPLING represents a significant de
parture from the many good books on sampling
which assume sophisticated statistical knowl
edge or extensive resources. The volume, which
abounds in practical examples of the kind that
researchers most frequently encounter in their
work, is intended for the very large majority of
survey users who have only limited statistical
backgrounds and resources but who wish to
maximize the usefulness of the data they ob
tain. The author carefully outlines a broad ar
ray of relatively simple procedures that are
much less expensive than, and quite comparable
to, the most precise methods now in current
use.
APPLI ED SAMPLING will be an invaluable prac
tical asset to all users of survey research meth
ods — sociologists, market researchers, educa
tional researchers, program evaluators, and
students of these topics.
Jacket design by Claire Counihan
Applied Sampling
This is a volume of
Quantitative Studies in Social Relations
Consulting Editor: Peter H. Rossi, University of Massachusetts,
Amherst, Massachusetts
A complete list of titles in this series appears at the end of this volume.
A p p lie d
S a m p lin g
Seym our Sudm an
Departments of Business Administration
and Sociology and the Survey Research Laboratory
University of Illinois, Urbana-Champaign
Urbana, Illinois
ACADEMIC PRESS New York San Francisco London
A Subsidiary of Harcourt Brace Jovanovich, Publishers
Copyright © 1976, by Academic Press, Inc.
ALL RIGHTS RESERVED.
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TRANSMITTED IN ANY FORM OR BY ANY MEANS, ELECTRONIC
OR MECHANICAL, INCLUDING PHOTOCOPY, RECORDING, OR ANY
INFORMATION STORAGE AND RETRIEVAL SYSTEM, WITHOUT
PERMISSION IN WRITING FROM THE PUBLISHER.
ACADEMIC PRESS, INC.
Ill Fifth Avenue, New York, New York 10003
United Kingdom Edition published by
ACADEMIC PRESS, INC. (LONDON) LTD.
24/28 Oval Road, London NW1
Library of Congress Cataloging in Publication Data
Sudman, Seymour.
Applied sampling.
(Quantitative studies in social relations)
Bibliography: p.
Includes index.
1. Social surveys. 2. Social science research -
United States. 3. Sampling (Statistics) I. Title.
HN29.S688 309'.07'23 75-34460
ISBN 0-12-675750-X
i
PRINTED IN THE UNITED STATES OF AMERICA
Contents
Preface ix
Deciding How to Do the Study 1
1.1 Introduction 1
1.2 How Good Must the Sample Be? 2
1.3 Inappropriate Sample Designs 9
1.4 The Use of Biased Samples for Screening 10
1.5 Defining the Population 11
1.6 Problems with Overdefinipg the Population 14
1.7 Operational Definitions of the Population 14
1.8 What Field Methods Should Be Used 15
1.9 The Uses of Combined Methods 18
1.10 Should an Existing Survey Organization Be Used? 18
1.11 Unusual Populations 19
1.12 Sampling from Limited Geographic Areas 20
1.13 Selecting Places for Experiments 21
1.14 The Use of Local Areas for Natural Experiments 22
1.15 Summary 22
1.16 Additional Reading 23
Small-Scale Sampling with Limited Resources 25
2.1 Introduction 25
2.2 A Credibility Scale 26
2.3 Examples 30
v
CONTENTS
2.4 Summary 46
2.5 Additional Reading 47
Simple and Pseudo-Simple Random Sampling 49
3.1 Random Numbers 50
3.2 Systematic Sampling 52
3.3 Are Systematic Samples Simple Random Samples? 56
3.4 The Uses and Limitations of Lists 58
3.5 Blanks and Ineligibles on Lists 59
3.6 Duplications 61
3.7 Omissions from Lists 63
3.8 The Use of Telephone Directories and Random Digit Dialing 64
3.9 Summary 66
3.10 Additional Reading 66
Cluster Sampling 69
4.1 Kinds of Clusters 69
4.2 The Costs of Gathering Survey Data 71
4.3 Increases in Sample Variability Due to Clustering 73
4.4 The Effects of Cluster Size on Sampling Error 76
4.5 Optimum Cluster Sizes 78
4.6 Optimum Cluster Sizes within PSUs 81
4.7 Clustering within the Block or Segment 82
4.8 Summary 83
4.9 Additional Reading 84
How Big Should the Sample Be? 85
5.1 Introduction 85
5.2 Current Sample Sizes Used 86
5.3 Sample Size Determination in Special Cases 87
5.4 Comparison of Classical and Bayesian Procedures for Sample Size Selection 89
5.5 The Value of Information 90
5.6 Value of Information for Decisions for Maximizing Gains 91
5.7 Long-Run Meaning of Value of Information 94
5.8 Resource Allocation by Public Agencies for Basic Research 95
5.9 Optimum Sample Size for a Basic Research Project 98
5.10 Optimum Sample Size for a Two-Action Linear Decision 99
5.11 Should There Be Any Sampling at All? 102
5.12 Summary 104
5.13 Additional Reading 105
Stratified Sampling 107
6.1 Appropriate and Inappropriate Uses of Stratification 108
6.2 The Strata Are of Primary Interest 110
6.3 Variances Differ between Strata 112
6.4 Costs Differ by Strata 118
CONTENTS vii
6.5 Prior Information Differs by Strata 121
6.6 Both Fixed and Variable Costs Differ by Strata with Prior Information 123
6.7 Estimation Procedures and Sampling Error Computation for
Disproportionate Samples 126
6.8 Summary 130
6.9 Additional Reading 130
Multistage Samples 131
7.1 Area Sampling 131
7.2 Sampling with Probabilities Proportionate to Size 134
7.3 How Sampling PPS Gives Equal Sample Sizes in Noncertainty Clusters 138
7.4 Sampling PPS at Several Stages 139
7.5 The Difference between Sampling Clusters PPS and Stratifying by Size 146
7.6 When Not to Sample PPS 146
7.7 Why Sampling PPS Does Not Mean Exactly Equal Sample Clusters 148
7.8 Obtaining Published Data for Sample Selection 150
7.9 The Use of Lists in Multistage Sampling 152
7.10 Obtaining New Lists 153
7.11 Summary 170
7.12 Additional Reading 170
Sampling Variance Estimation from Complex Samples 171
8.1 What Are Sampling Variances? 171
8.2 Pseudoreplication 178
8.3 Variance Estimates from Systematic Samples with Implicit Stratification 182
8.4 Measuring Design Effects 184
8.5 Variance Computation in Special Cases 186
8.6 Combining Variance Estimates with Prior Information 188
8.7 Summary 189
8.8 Additional Reading 189
Special Topics in Sampling 191
9.1 Probability Sampling with Quotas 191
9.2 Assumptions Underlying Probability Sampling with Quotas 193
9.3 Respondent Characteristics Related to Availability for Interviewing 195
9.4 Sample Biases Due to Quota Procedures 198
9.5 Costs of Probability Samples with Call-Backs and with Quotas 199
9.6 Screening for Rare Populations 200
9.7 Optimum Sampling Designs When Screening Costs Are Large 203
9.8 Estimating the Percentage of the Very Rare Population in a Cluster 205
9.9 Field Procedures for Screening 209
9.10 Snowball Sampling 210
9.11 Panel Sampling 212
9.12 Sample Cooperation in Consumer Panels 212
9.13 Sample Biases in Panels 213
9.14 Panel Maintenance Policies 218
9.15 Panel Clustering 220
viii CONTENTS
9.16 Sampling Variance Computations for Panels 221
9.17 Summary 221
9.18 Additional Reading 222
Appendix A Table of Random Digits 223
Appendix B Measures of Homogeneity p 227
Appendix C Unit Normal Loss Integral 231
Appendix D Nomograph for Computing Optimum Sample Size 232
References 235
Index 241
