Indirect Sampling (eBook)

Pierre Lavallee (Autor)

eBook Download: PDF

2009 | 2007
XVI, 256 Seiten
Springer New York (Verlag)
978-0-387-70782-2 (ISBN)

Infos

This book is the reference on indirect sampling and the generalised weight share method. It reviews the different developments done by the author on these subjects. In addition to the underlying theory, the book presents different possible applications that drive its interest. The reader will find in this book the answer to questions that come, inevitably, when working in a context of indirect sampling.

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Following the classical sampling theory, the survey statistician selects samples of people, businesses or others, in order to obtain the desired information. Drawing the samples is usually done by randomly selecting from a list representing the target population. In practice, this list is often not available. At best, the statistician only has access to a different list, indirectly related to the targeted population.The example of a survey of children where the statistician only has a list of adult persons is a typical case. In this case, the statistician first draws a sample of adults, and for each selected adult, the statistician then identifies his/her children. The survey is done from the latter. This is what is called indirect sampling.When indirect sampling is used jointly with the sampling of clusters of persons (families, for example), many complications arise for the survey statistician. One of the complications relates to the computation of the estimates from the survey. The production of estimates of simple totals or means can then become nightmares for the survey statistician. To solve this problem, the author proposes a simple solution, easy to implement, that is called the generalised weight share method.This book is the reference on indirect sampling and the generalised weight share method. It contains the different developments done by the author on these subjects. The theory surrounding them is presented, but also different possible applications that drive its interest. The reader will find in this book the answer to questions that come, inevitably, when working in a context of indirect sampling.

Inhalt

FOREWORD 7
PREFACE 9
TABLE OF CONTENTS 13
INTRODUCTION 17
1.1 REVIEW OF SAMPLING THEORY AND WEIGHTING 17
1.2 CLUSTER SAMPLING 20
1.3 INDIRECT SAMPLING 23
1.4 GENERALISED WEIGHT SHARE METHOD 26
DESCRIPTION AND USE OF THE GWSM 28
2.1 DESCRIPTION 28
2.2 USE 33
2.2.1 Indirect sampling for rare populations 34
2.2.2 Weighting using only the selection probabilities of the selected units 35
2.2.3 Weighting of populations related by complex links 35
2.2.4 Weighting of unlinked units 36
LITERATURE REVIEW 37
3.1 FIRST STEPS 37
3.2 FAIR SHARE METHOD 38
3.3 CONTRIBUTION OF ERNST (1989) 42
3.4 NETWORK SAMPLING 46
3.5 ADAPTIVE CLUSTER SAMPLING 51
3.6 SNOWBALL SAMPLING 56
PROPERTIES 58
4.1 BIAS AND VARIANCE 58
4.2 PARTICULAR CASE 1: CLUSTER SAMPLING 63
4.3 PARTICULAR CASE 2: CENSUS OF POPULATION UA 66
4.4 PARTICULAR CASE 3: CENSUS OF POPULATION UB 67
4.5 USE OF WEIGHTED LINKS 69
4.6 IMPROVEMENT OF THE ESTIMATOR 72
4.6.1 Conditional approach 72
4.6.2 Use of sufficient statistics 76
4.6.3 Obtaining optimal weighted links 78
OTHER GENERALISATIONS 90
5.1 TWO-STAGE INDIRECT SAMPLING 90
5.2 ARBITRARY ASPECT IN THE FORMATION OF CLUSTERS 96
5.2.1 Extreme case (i): population UB with a single cluster of size MB 97
5.2.2 Extreme case (ii): population UB with MB clusters of size 1 99
5.2.3 General case and discussion 102
APPLICATION IN LONGITUDINAL SURVEYS 117
6.1 SAMPLING DESIGN OF SLID 118
6.1.1 Initial sample 119
6.1.2 Supplementary sample 121
6.2 ESTIMATION WEIGHTS 123
6.3 USE OF THE GWSM IN OBTAINING ESTIMATION WEIGHTS 125
6.4 VARIANCE ESTIMATION 129
6.5 USE OF ANOTHER TYPE OF LINKS 130
GWSM AND CALIBRATION 133
7.1 REVIEW OF CALIBRATION 133
7.2 GWSM WITH CALIBRATION 140
7.3 PARTICULAR CASE 1: AUXILIARY VARIABLES COMING FROM UA 144
7.4 PARTICULAR CASE 2: AUXILIARY VARIABLES COMING FROM UB 148
7.4.1 Application of calibration before GWSM 148
7.4.2 Application of calibration after GWSM 150
7.4.3 Comparison of the two approaches 154
7.4.4 Simulation study 157
NON · RESPONSE 163
8.1 TYPES OF NON·RESPONSE 164
8.2 CORRECTING RESPONSE RATES 167
8.3 RESPONSE PROBABILITIES 169
8.4 TREATMENT OF NON-RESPONSE WITHIN SA 172
8.5 TREATMENT OF CLUSTER NON-RESPONSE 178
8.6 TREATMENT OF UNIT NON-RESPONSE 186
8.7 TREATMENT OF ERRORS IN LINKS IDENTIFICATION 195
8.7.1 Record linkage 198
8.7.2 Modelling 199
GWSM AND RECORD LINKAGE 206
9.1 RECORD LINKAGE 207
9.2 GWSM ASSOCIATED WITH RECORD LINKAGE 210
9.2.1 Approach 1: use all non-zero links with their respective linkage weights 212
9.2.2 Approach 2: use all non- zero links above a given threshold 215
9.2.3 Approach 3: choose the links randomly 217
9.2.4 Some remarks 221
9.3 SIMULATION STUDY 222
9.3.1 Data used 223
9.3.2 Sampling plan 225
9.3.3 Results and discussion 226
CONCLUSION 236
NOTATIONS 241
BIBLIOGRAPHY 245
INDEX 253

Produkt-Details

• Erscheint lt. Verlag: 21.12.2009
• Reihe/Serie: Springer Series in Statistics
• Reihe/Serie: Springer Series in Statistics
• Zusatzinfo: XVI, 256 p.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Studium ► Querschnittsbereiche ► Prävention / Gesundheitsförderung
• Themenwelt: Naturwissenschaften
• Themenwelt: Sozialwissenschaften ► Politik / Verwaltung
• Themenwelt: Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung
• Themenwelt: Technik
• Schlagworte: clusters • Links • Production • Survey Sampling • unbiasedness • weighting
• ISBN-10: 0-387-70782-4 / 0387707824
• ISBN-13: 978-0-387-70782-2 / 9780387707822