Sampling 3rd Edition

Informationen zum Autor 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). Klappentext Praise for the Second Edition"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"Well-written . . . an excellent book on an important subject. Highly recommended." --Choice"An ideal reference for scientific researchers and other professionals who use sampling." --Zentralblatt MathFeatures new developments in the field combined with all aspects of obtaining, interpreting, and using sample dataSampling provides an up-to-date treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. This Third Edition retains the general organization of the two previous editions, but incorporates extensive new material--sections, exercises, and examples--throughout. Inside, readers will find all-new approaches to explain the various techniques in the book; new figures to assist in better visualizing and comprehending underlying concepts such as the different sampling strategies; computing notes for sample selection, calculation of estimates, and simulations; and more.Organized into six sections, the book covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio and regression estimation; sufficient data, model, and design in practical sampling; useful designs such as stratified, cluster and systematic, multistage, double and network sampling; detectability methods for elusive populations; spatial sampling; and adaptive sampling designs.Featuring a broad range of topics, Sampling, Third Edition serves as a valuable reference on useful sampling and estimation methods for researchers in various fields of study, including biostatistics, ecology, and the health sciences. The book is also ideal for courses on statistical sampling at the upper-undergraduate and graduate levels. Zusammenfassung Praise for the Second Edition "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 "Well-written... an excellent book on an important subject. Highly recommended. Inhaltsverzeichnis Preface xv Preface to the Second Edition xvii Preface to the First Edition xix 1 Introduction 1 1.1 Basic Ideas of Sampling and Estimation, 2 1.2 Sampling Units, 4 1.3 Sampling and Nonsampling Errors, 5 1.4 Models in Sampling, 5 1.5 Adaptive and Nonadaptive Designs, 6 1.6 Some Sampling History, 7 PART I BASIC SAMPLING 9 2 Simple Random Sampling 11 2.1 Selecting a Simple Random Sample, 11 2.2 Estimating the Population Mean, 13 2.3 Estimating the Population Total, 16 2.4 Some Underlying Ideas, 17 2.5 Random Sampling with Replacement, 19 2.6 Derivations for Random Sampling, 20 2.7 Model-Based Approach to Sampling, 22 2.8 Computing Notes, 26 Entering Data in R, 26 Sample Estimates, 27 Simulation, 28 Further Comments on the Use of Simulation, 32 Exercises, 35 3 Confidence Intervals 39 3.1 Confidence Interval for the Population Mean or Total, 39 3.2 Finite-Population Central Limit Theorem, 41 3.3 Sampling Distributions, 43 3.4 Computing Notes, 44 Confidence Interval Computation, 44

List of contents

Preface xv
 
Preface to the Second Edition xvii
 
Preface to the First Edition xix
 
1 Introduction 1
 
PART I BASIC SAMPLING 9
 
2 Simple Random Sampling 11
 
Entering Data in R, 26
 
Sample Estimates, 27
 
Simulation, 28
 
Further Comments on the Use of Simulation, 32
 
Exercises, 35
 
3 Confidence Intervals 39
 
Confidence Interval Computation, 44
 
Simulations Illustrating the Approximate Normality of a Sampling Distribution with Small n and N, 45
 
Daily Precipitation Data, 46
 
Exercises, 50
 
4 Sample Size 53
 
Exercises, 56
 
5 Estimating Proportions, Ratios, and Subpopulation Means 57
 
Estimating a Subpopulation Mean, 63
 
Estimating a Proportion for a Subpopulation, 64
 
Estimating a Subpopulation Total, 64
 
Exercises, 65
 
6 Unequal Probability Sampling 67
 
Writing an R Function to Simulate a Sampling Strategy, 82
 
Comparing Sampling Strategies, 84
 
Exercises, 88
 
PART II MAKING THE BEST USE OF SURVEY DATA 91
 
7 Auxiliary Data and Ratio Estimation 93
 
Types of Estimators for a Ratio, 109
 
Exercises, 112
 
8 Regression Estimation 115
 
Exercises, 124
 
9 The Sufficient Statistic in Sampling 125
 
10 Design and Model 131
 
PART III SOME USEFUL DESIGNS 139
 
11 Stratified Sampling 141
 
With Any Stratified Design, 142
 
With Stratified Random Sampling, 143
 
With Any Stratified Design, 144
 
With Stratified Random Sampling, 144
 
Optimum Allocation, 149
 
Poststratification Variance, 150
 
Exercises, 155
 
12 Cluster and Systematic Sampling 157
 
Unbiased Estimator, 159
 
Ratio Estimator, 160
 
Hansen-Hurwitz (PPS) Estimator, 161
 
Horvitz-Thompson Estimator, 161
 
Exercises, 169
 
13 Multistage Designs 171
 
Unbiased Estimator, 173
 
Ratio Estimator, 175
 
Unbiased Estimator, 179
 
Ratio Estimator, 181
 
Probability-Proportional-to-Size Sampling, 181
 
More Than Two Stages, 181
 
Exercises, 182
 
14 Double or Two-Phase Sampling 183
 
Approximate Mean and Variance: Ratio Estimation, 188
 
Optimum Allocation for Ratio Estimation, 189
 
Expected Value and Variance: Stratification, 189
 
Nonresponse, Selection Bias, or Volunteer Bias, 191
 
Double Sampling to Adjust for Nonresponse: Callbacks, 192
 
Response Modeling and Nonresponse Adjustments, 193
 
Exercises, 197
 
PART IV METHODS FOR ELUSIVE AND HARD-TO-DETECT POPULATIONS 199
 
15 Network Sampling and Link-Tracing Designs 201
 
Multiplicity Estimator, 202
 
Horvitz-Thompson Estimator, 204
 
Exercises, 213
 
16 Detectability and Sampling 215
 
Exercises, 227
 
17 Line and Point Transects 229
 
Estimating f (0) by the Kernel Method, 237
 
Fourier Series Method, 239
 
Unbiased Estimator, 241
 
Ratio Estimator, 243
 
Line Transects and Detectability Functions, 247
 
Single Transect, 249
 
Average Detectability, 249
 
Random Transect, 250
 
Average Detectability and Effective Area, 251
 
Effect of Estimating Detectability, 252
 
Probability Density Function of an Observed Distance, 253
 
Estimation of Individual Detectabilities, 256
 
Exercise, 260
 
18 Capture-Recapture Sampling 263
 
Random Sampling with Replacem

Product details

• Authors: Thompson, Steven K Thompson, Steven K. Thompson
• Publisher: Blackwell Scientific Publishers Ltd
• Languages: English
• Product format: Hardback
• Released: 29.02.2012
• EAN: 9780470402313
• ISBN: 978-0-470-40231-3
• Dimensions: 165 mm x 242 mm x 30 mm
• Series: Wiley Series in Probability and Statistics; Wiley Desktop Editions; Wiley Desktop Editions
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Statistik, Psychologie, Stichprobe, Statistics, Psychology, Psychologische Methoden, Forschung u. Statistik, Psychological Methods, Research & Statistics, Methoden der Daten- u. Stichprobenerhebung, Survey Research Methods & Sampling, Evaluation & Research Methods, Evaluierung u. Researchmethoden