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  • Edition: 3rd
  • Format: Hardcover
  • Copyright: 2012-03-13
  • Publisher: Wiley
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The Third Edition retains the general organization of the prior two editions, but it incorporates new material throughout the text.  The book is organized into six parts: Part I covers basic sampling from simple random sampling to unequal probability sampling; Part II treats the use of auxiliary data with ratio and regression estimation and looks at the ideas of sufficient data, model, and design in practical sampling; Part III covers major useful designs such as stratified, cluster and systematic, multistage, and double and network sampling; Part IV examines detectability methods for elusive populations, and basic problems in detectability, visibility, and catchability are discussed; Part V concerns spatial sampling with the prediction methods of geostatistics, considerations of efficient spatial designs, and comparisons of different observational methods including plot shapes and detection aspects; and Part VI introduces adaptive sampling designs in which the sampling procedure depends on what is observed during the survey.  For this new edition, the author has focused on thoroughly updating the book with a special emphasis on the first 14 chapters since these topics are invariably covered in basic sampling courses.  The author has also implemented new approaches to explain the various techniques in the book, and as a result, new examples and explanations have been added throughout.  In an effort to improve the presentation and visualization of the book, new figures as well as replacement figures for previously existing figures have been added.  This book has continuously stood out from other sampling texts since the figures evoke the idea of each sampling design.  The new figures will help readers to better visualize and understand the underlying concepts such as the different sampling strategies.

Author Biography

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).

Table of Contents

Prefacep. xv
Preface to the Second Editionp. xvii
Preface to the First Editionp. xix
Introductionp. 1
Basic Ideas of Sampling and Estimationp. 2
Sampling Unitsp. 4
Sampling and Nonsampling Errorsp. 5
Models in Samplingp. 5
Adaptive and Nonadaptive Designsp. 6
Some Sampling Historyp. 7
Basic Samplingp. 9
Simple Random Samplingp. 11
Selecting a Simple Random Samplep. 11
Estimating the Population Meanp. 13
Estimating the Population Totalp. 16
Some Underlying Ideasp. 17
Random Sampling with Replacementp. 19
Derivations for Random Samplingp. 20
Model-Based Approach to Samplingp. 22
Computing Notesp. 26
Entering Data in Rp. 26
Sample Estimatesp. 27
Simulationp. 28
Further Comments on the Use of Simulationp. 32
Exercisesp. 35
Confidence Intervalsp. 39
Confidence Interval for the Population Mean or Totalp. 39
Finite-Population Central Limit Theoremp. 41
Sampling Distributionsp. 43
Computing Notesp. 44
Confidence Interval Computationp. 44
Simulations Illustrating the Approximate Normality of a Sampling Distribution with Small n and Np. 45
Daily Precipitation Datap. 46
Exercisesp. 50
Sample Sizep. 53
Sample Size for Estimating a Population Meanp. 54
Sample Size for Estimating a Population Totalp. 54
Sample Size for Relative Precisionp. 55
Exercisesp. 56
Estimating Proportions, Ratios, and Subpopulation Meansp. 57
Estimating a Population Proportionp. 58
Confidence Interval for a Proportionp. 58
Sample Size for Estimating a Proportionp. 59
Sample Size for Estimating Several Proportions Simultaneouslyp. 60
Estimating a Ratiop. 62
Estimating a Mean, Total, or Proportion of a Subpopulationp. 62
Estimating a Subpopulation Meanp. 63
Estimating a Proportion for a Subpopulationp. 64
Estimating a Subpopulation Totalp. 64
Exercisesp. 65
Unequal Probability Samplingp. 67
Sampling with Replacement: The Hansen-Hurwitz Estimatorp. 67
Any Design: The Horvitz-Thompson Estimatorp. 69
Generalized Unequal-Probability Estimatorp. 72
Small Population Examplep. 73
Derivations and Commentsp. 75
Computing Notesp. 78
Writing an R Function to Simulate a Sampling Strategyp. 82
Comparing Sampling Strategiesp. 84
Exercisesp. 88
Making The Best Use Of Survey Datap. 91
Auxiliary Data and Ratio Estimationp. 93
Ratio Estimatorp. 94
Small Population Illustrating Biasp. 97
Derivations and Approximations for the Ratio Estimatorp. 99
Finite-Population Central Limit Theorem for the Ratio Estimatorp. 101
Ratio Estimation with Unequal Probability Designsp. 102
Models in Ratio Estimationp. 105
Types of Estimators for a Ratiop. 109
Design Implications of Ratio Modelsp. 109
Computing Notesp. 110
Exercisesp. 112
Regression Estimationp. 115
Linear Regression Estimatorp. 116
Regression Estimation with Unequal Probability Designsp. 118
Regression Modelp. 119
Multiple Regression Modelsp. 120
Design Implications of Regression Modelsp. 123
Exercisesp. 124
The Sufficient Statistic in Samplingp. 125
The Set of Distinct, Labeled Observationsp. 125
Estimation in Random Sampling with Replacementp. 126
Estimation in Probability-Proportional-to-Size Samplingp. 127
Comments on the Improved Estimatesp. 128
Design and Modelp. 131
Uses of Design and Model in Samplingp. 131
Connections between the Design and Model Approachesp. 132
Some Commentsp. 134
Likelihood Function in Samplingp. 135
Some Useful Designsp. 139
Stratified Samplingp. 141
Estimating the Population Totalp. 142
With Any Stratified Designp. 142
With Stratified Random Samplingp. 143
Estimating the Population Meanp. 144
With Any Stratified Designp. 144
With Stratified Random Samplingp. 144
Confidence Intervalsp. 145
The Stratification Principlep. 146
Allocation in Stratified Random Samplingp. 146
Poststratificationp. 148
Population Model for a Stratified Populationp. 149
Derivations for Stratified Samplingp. 149
Optimum Allocationp. 149
Poststratification Variancep. 150
Computing Notesp. 151
Exercisesp. 155
Cluster and Systematic Samplingp. 157
Primary Units Selected by Simple Random Samplingp. 159
Unbiased Estimatorp. 159
Ratio Estimatorp. 160
Primary Units Selected with Probabilities Proportional to Sizep. 161
Hansen-Hurwitz (PPS) Estimatorp. 161
Horvitz-Thompson Estimatorp. 161
The Basic Principlep. 162
Single Systematic Samplep. 162
Variance and Cost in Cluster and Systematic Samplingp. 163
Computing Notesp. 166
Exercisesp. 169
Multistage Designsp. 171
Simple Random Sampling at Each Stagep. 173
Unbiased Estimatorp. 173
Ratio Estimatorp. 175
Primary Units Selected with Probability Proportional to Sizep. 176
Any Multistage Design with Replacementp. 177
Cost and Sample Sizesp. 177
Derivations for Multistage Designsp. 179
Unbiased Estimatorp. 179
Ratio Estimatorp. 181
Probability-Proportional-to-Size Samplingp. 181
More Than Two Stagesp. 181
Exercisesp. 182
Double or Two-Phase Samplingp. 183
Ratio Estimation with Double Samplingp. 184
Allocation in Double Sampling for Ratio Estimationp. 186
Double Sampling for Stratificationp. 186
Derivations for Double Samplingp. 188
Approximate Mean and Variance: Ratio Estimationp. 188
Optimum Allocation for Ratio Estimationp. 189
Expected Value and Variance: Stratificationp. 189
Nonsampling Errors and Double Samplingp. 190
Nonresponse, Selection Bias, or Volunteer Biasp. 191
Double Sampling to Adjust for Nonresponse: Callbacksp. 192
Response Modeling and Nonresponse Adjustmentsp. 193
Computing Notesp. 195
Exercisesp. 197
Methods For Elusive And Hard-To-Detect Populationsp. 199
Network Sampling and Link-Tracing Designsp. 201
Estimation of the Population Total or Meanp. 202
Multiplicity Estimatorp. 202
Horvitz-Thompson Estimatorp. 204
Derivations and Commentsp. 207
Stratification in Network Samplingp. 208
Other Link-Tracing Designsp. 210
Computing Notesp. 212
Exercisesp. 213
Detectability and Samplingp. 215
Constant Detectability over a Regionp. 215
Estimating Detectabilityp. 217
Effect of Estimated Detectabilityp. 218
Detectability with Simple Random Samplingp. 219
Estimated Detectability and Simple Random Samplingp. 220
Sampling with Replacementp. 222
Derivationsp. 222
Unequal Probability Sampling of Groups with Unequal Detection Probabilitiesp. 224
Derivationsp. 225
Exercisesp. 227
Line and Point Transectsp. 229
Density Estimation Methods for Line Transectsp. 230
Narrow-Strip Methodp. 230
Smooth-by-Eye Methodp. 233
Parametric Methodsp. 234
Nonparametric Methodsp. 237
Estimating f (0) by the Kernel Methodp. 237
Fourier Series Methodp. 239
Designs for Selecting Transectsp. 240
Random Sample of Transectsp. 240
Unbiased Estimatorp. 241
Ratio Estimatorp. 243
Systematic Selection of Transectsp. 244
Selection with Probability Proportional to Lengthp. 244
Note on Estimation of Variance for the Kernel Methodp. 246
Some Underlying Ideas about Line Transectsp. 247
Line Transects and Detectability Functionsp. 247
Single Transectp. 249
Average Detectabilityp. 249
Random Transectp. 250
Average Detectability and Effective Areap. 251
Effect of Estimating Detectabilityp. 252
Probability Density Function of an Observed Distancep. 253
Detectability Imperfect on the Line or Dependent on Sizep. 255
Estimation Using Individual Detectabilitiesp. 255
Estimation of Individual Detectabilitiesp. 256
Detectability Functions other than Line Transectsp. 257
Variable Circular Plots or Point Transectsp. 259
Exercisep. 260
Capture-Recapture Samplingp. 263
Single Recapturep. 264
Models for Simple Capture-Recapturep. 266
Sampling Design in Capture-Recapture: Ratio Variance Estimatorp. 267
Random Sampling with Replacement of Detectability Unitsp. 269
Random Sampling without Replacementp. 270
Estimating Detectability with Capture-Recapture Methodsp. 271
Multiple Releasesp. 272
More Elaborate Modelsp. 273
Exercisep. 273
Line-Intercept Samplingp. 275
Random Sample of Lines: Fixed Directionp. 275
Lines of Random Position and Directionp. 280
Exercisesp. 282
Spatial Samplingp. 283
Spatial Prediction or Krigingp. 285
Spatial Covariance Functionp. 286
Linear Prediction (Kriging)p. 286
Variogramp. 289
Predicting the Value over a Regionp. 291
Derivations and Commentsp. 292
Computing Notesp. 296
Exercisep. 299
Spatial Designsp. 301
Design for Local Predictionp. 302
Design for Prediction of Mean of Regionp. 302
Plot Shapes and Observational Methodsp. 305
Observations from Plotsp. 305
Observations from Detectability Unitsp. 307
Comparisons of Plot Shapes and Detectability Methodsp. 308
Adaptive Samplingp. 313
Adaptive Sampling Designsp. 315
Adaptive and Conventional Designs and Estimatorsp. 315
Brief Survey of Adaptive Samplingp. 316
Adaptive Cluster Samplingp. 319
Designsp. 321
Initial Simple Random Sample without Replacementp. 322
Initial Random Sample with Replacementp. 323
Estimatorsp. 323
Initial Sample Meanp. 323
Estimation Using Draw-by-Draw Intersectionsp. 323
Estimation Using Initial Intersection Probabilitiesp. 325
When Adaptive Cluster Sampling Is Better than Simple Random Samplingp. 327
Expected Sample Size, Cost, and Yieldp. 328
Comparative Efficiencies of Adaptive and Conventional Samplingp. 328
Further Improvement of Estimatorsp. 330
Derivationsp. 333
Data for Examples and Figuresp. 336
Exercisesp. 337
Systematic and Strip Adaptive Cluster Samplingp. 339
Designsp. 341
Estimatorsp. 343
Initial Sample Meanp. 343
Estimator Based on Partial Selection Probabilitiesp. 344
Estimator Based on Partial Inclusion Probabilitiesp. 345
Calculations for Adaptive Cluster Sampling Strategiesp. 347
Comparisons with Conventional Systematic and Cluster Samplingp. 349
Derivationsp. 350
Example Datap. 352
Exercisesp. 352
Stratified Adaptive Cluster Samplingp. 353
Designsp. 353
Estimatorsp. 356
Estimators Using Expected Numbers of Initial Intersectionsp. 357
Estimator Using Initial Intersection Probabilitiesp. 359
Comparisons with Conventional Stratified Samplingp. 362
Further Improvement of Estimatorsp. 364
Example Datap. 367
Exercisesp. 367
Answers to Selected Exercisesp. 369
Referencesp. 375
Author Indexp. 395
Subject Indexp. 399
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