Sampling / Edition 1

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Estimating an elusive human population, estimating the abundance of an animal population, predicting the amount of fossil-fuel resource at a new site, or estimating the prevalence of a rare disease requires statistical methods that go beyond the material traditionally found in sampling texts. Designed specifically for scientific researchers and others who use sampling, this important reference is the first to explore the host of sampling methods useful for investigating populations that are inherently difficult to sample, elusive, rare, clustered, or hard to detect. Balancing both classical and modern sampling methods, Sampling offers systematic, thorough, and broad-based coverage of basic and standard sampling design and estimation methods. Organized into six parts containing twenty-six chapters, the book is a comprehensive one-volume seminar on using sampling methods to develop effective sampling designs for real life situations. In a clear progressive format, the book examines basic sampling from simple random sampling to unequal probability sampling in Part 1. The use of auxiliary data with ratio and regression estimation is discussed in Part 2 as well as the ideas of sufficient data and of model and design in practical sampling. Part 3 covers major useful designs including stratified, cluster systematic, multistage, double, and network sampling. Part 4 examines detectability methods for elusive populations, focusing on detectability visibility and catchability as well as specific methods of line transects, variable circular plots, capture-recapture, and line intercept sampling. Spatial sampling is covered in Part 5, with discussion of prediction methods of geostatistics, efficient spatial designs, and comparisons of different observational methods including plot shapes and detection aspects. Part 6 introduces adaptive sampling designs, illustrating how the adaptive cluster sampling designs described are highly effective for sampling rare, clustered populat
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Editorial Reviews

From The Critics
This text treats both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. This second edition includes descriptions of new developments in the field, a wider range of approaches to common problems, historical notes, and increased coverage of adjusting for nonsampling errors, the use of link-tracing designs, and of methods combining design and model-based approaches. Material is updated to show how sampling methods function in such fields as the biological, environmental, social, and health sciences, and with new material on sampling the Internet. Thompson teaches statistics at the Pennsylvania State University. Annotation c. Book News, Inc., Portland, OR (
A textbook for a graduate or upper-level undergraduate course in sampling. Describes advanced methods by which researchers can pursue difficult sampling problems, such as counting an elusive human or animal population, predicting the amount of fossil-fuel resource at a new site, or estimating the prevalence of a rare disease. Annotation c. Book News, Inc., Portland, OR (
From the Publisher
"This is an informative and clearly written book that will serve as a useful reference for researchers and as an introduction for students…" (Statistics in Medical Research, October 2005)

"...treats both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations." (SciTech Book News, Vol. 26, No. 2, June 2002)

"...a well-written and expanded new excellent book on an important subject. Highly recommended..." (Choice, Vol. 40, No. 2, October 2002)

"This book has never had a competitor. It is the only book that takes a broad approach to sampling...any good personal statistics library should include a copy of this book." (Technometrics, Vol. 44, No. 4, November 2002)

" ideal reference for scientific researchers and other professionals who use sampling..."(Zentralblatt Math, Vol.1002, No.02, 2003)

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Product Details

  • ISBN-13: 9780471540458
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 1/28/1992
  • Series: Wiley Series in Probability and Statistics Series, #272
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 360
  • Product dimensions: 6.47 (w) x 9.59 (h) x 1.08 (d)

Meet the Author

Steven K. Thompson, PhD, is Shrum Chair in Science and Professor of Statistics at the Simon Fraser University. During his career, he has served on the faculties of the Pennsylvania State University, the University of Auckland, and the University of Alaska. He is also the coauthor of Adaptive Sampling (Wiley).

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Table of Contents

Preface to the Second Edition
Preface to the First Edition
1 Introduction 1
Pt. I Basic Sampling 9
2 Simple Random Sampling 11
3 Confidence Intervals 29
4 Sample Size 35
5 Estimating Proportions, Ratios, and Subpopulation Means 39
6 Unequal Probability Sampling 51
Pt. II Making the Best Use of Survey Data 65
7 Auxiliary Data and Ratio Estimation 67
8 Regression Estimation 89
9 The Sufficient Statistic in Sampling 101
10 Design and Model 107
Pt. III Some Useful Designs 115
11 Stratified Sampling 117
12 Cluster and Systematic Sampling 129
13 Multistage Designs 143
14 Double or Two-Phase Sampling 157
Pt. IV Methods for Elusive and Hard-to-Detect Populations 171
15 Network Sampling and Link-Tracing Designs 173
16 Detectability and Sampling 185
17 Line and Point Transects 199
18 Capture-Recapture Sampling 233
19 Line-Intercept Sampling 245
Pt. V Spatial Sampling 255
20 Spatial Prediction or Kriging 257
21 Spatial Designs 271
22 Plot Shapes and Observational Methods 275
Pt. VI Adaptive Sampling 283
23 Adaptive Sampling Designs 285
24 Adaptive Cluster Sampling 289
25 Systematic and Strip Adaptive Cluster Sampling 309
26 Stratified Adaptive Cluster Sampling 323
Answers to Selected Exercises 339
References 343
Author Index 361
Subject Index 365
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