Preface | p. xv |

Preface to the Second Edition | p. xvii |

Preface to the First Edition | p. xix |

Introduction | p. 1 |

Basic Ideas of Sampling and Estimation | p. 2 |

Sampling Units | p. 4 |

Sampling and Nonsampling Errors | p. 5 |

Models in Sampling | p. 5 |

Adaptive and Nonadaptive Designs | p. 6 |

Some Sampling History | p. 7 |

Basic Sampling | p. 9 |

Simple Random Sampling | p. 11 |

Selecting a Simple Random Sample | p. 11 |

Estimating the Population Mean | p. 13 |

Estimating the Population Total | p. 16 |

Some Underlying Ideas | p. 17 |

Random Sampling with Replacement | p. 19 |

Derivations for Random Sampling | p. 20 |

Model-Based Approach to Sampling | p. 22 |

Computing Notes | p. 26 |

Entering Data in R | p. 26 |

Sample Estimates | p. 27 |

Simulation | p. 28 |

Further Comments on the Use of Simulation | p. 32 |

Exercises | p. 35 |

Confidence Intervals | p. 39 |

Confidence Interval for the Population Mean or Total | p. 39 |

Finite-Population Central Limit Theorem | p. 41 |

Sampling Distributions | p. 43 |

Computing Notes | p. 44 |

Confidence Interval Computation | p. 44 |

Simulations Illustrating the Approximate Normality of a Sampling Distribution with Small n and N | p. 45 |

Daily Precipitation Data | p. 46 |

Exercises | p. 50 |

Sample Size | p. 53 |

Sample Size for Estimating a Population Mean | p. 54 |

Sample Size for Estimating a Population Total | p. 54 |

Sample Size for Relative Precision | p. 55 |

Exercises | p. 56 |

Estimating Proportions, Ratios, and Subpopulation Means | p. 57 |

Estimating a Population Proportion | p. 58 |

Confidence Interval for a Proportion | p. 58 |

Sample Size for Estimating a Proportion | p. 59 |

Sample Size for Estimating Several Proportions Simultaneously | p. 60 |

Estimating a Ratio | p. 62 |

Estimating a Mean, Total, or Proportion of a Subpopulation | p. 62 |

Estimating a Subpopulation Mean | p. 63 |

Estimating a Proportion for a Subpopulation | p. 64 |

Estimating a Subpopulation Total | p. 64 |

Exercises | p. 65 |

Unequal Probability Sampling | p. 67 |

Sampling with Replacement: The Hansen-Hurwitz Estimator | p. 67 |

Any Design: The Horvitz-Thompson Estimator | p. 69 |

Generalized Unequal-Probability Estimator | p. 72 |

Small Population Example | p. 73 |

Derivations and Comments | p. 75 |

Computing Notes | p. 78 |

Writing an R Function to Simulate a Sampling Strategy | p. 82 |

Comparing Sampling Strategies | p. 84 |

Exercises | p. 88 |

Making The Best Use Of Survey Data | p. 91 |

Auxiliary Data and Ratio Estimation | p. 93 |

Ratio Estimator | p. 94 |

Small Population Illustrating Bias | p. 97 |

Derivations and Approximations for the Ratio Estimator | p. 99 |

Finite-Population Central Limit Theorem for the Ratio Estimator | p. 101 |

Ratio Estimation with Unequal Probability Designs | p. 102 |

Models in Ratio Estimation | p. 105 |

Types of Estimators for a Ratio | p. 109 |

Design Implications of Ratio Models | p. 109 |

Computing Notes | p. 110 |

Exercises | p. 112 |

Regression Estimation | p. 115 |

Linear Regression Estimator | p. 116 |

Regression Estimation with Unequal Probability Designs | p. 118 |

Regression Model | p. 119 |

Multiple Regression Models | p. 120 |

Design Implications of Regression Models | p. 123 |

Exercises | p. 124 |

The Sufficient Statistic in Sampling | p. 125 |

The Set of Distinct, Labeled Observations | p. 125 |

Estimation in Random Sampling with Replacement | p. 126 |

Estimation in Probability-Proportional-to-Size Sampling | p. 127 |

Comments on the Improved Estimates | p. 128 |

Design and Model | p. 131 |

Uses of Design and Model in Sampling | p. 131 |

Connections between the Design and Model Approaches | p. 132 |

Some Comments | p. 134 |

Likelihood Function in Sampling | p. 135 |

Some Useful Designs | p. 139 |

Stratified Sampling | p. 141 |

Estimating the Population Total | p. 142 |

With Any Stratified Design | p. 142 |

With Stratified Random Sampling | p. 143 |

Estimating the Population Mean | p. 144 |

With Any Stratified Design | p. 144 |

With Stratified Random Sampling | p. 144 |

Confidence Intervals | p. 145 |

The Stratification Principle | p. 146 |

Allocation in Stratified Random Sampling | p. 146 |

Poststratification | p. 148 |

Population Model for a Stratified Population | p. 149 |

Derivations for Stratified Sampling | p. 149 |

Optimum Allocation | p. 149 |

Poststratification Variance | p. 150 |

Computing Notes | p. 151 |

Exercises | p. 155 |

Cluster and Systematic Sampling | p. 157 |

Primary Units Selected by Simple Random Sampling | p. 159 |

Unbiased Estimator | p. 159 |

Ratio Estimator | p. 160 |

Primary Units Selected with Probabilities Proportional to Size | p. 161 |

Hansen-Hurwitz (PPS) Estimator | p. 161 |

Horvitz-Thompson Estimator | p. 161 |

The Basic Principle | p. 162 |

Single Systematic Sample | p. 162 |

Variance and Cost in Cluster and Systematic Sampling | p. 163 |

Computing Notes | p. 166 |

Exercises | p. 169 |

Multistage Designs | p. 171 |

Simple Random Sampling at Each Stage | p. 173 |

Unbiased Estimator | p. 173 |

Ratio Estimator | p. 175 |

Primary Units Selected with Probability Proportional to Size | p. 176 |

Any Multistage Design with Replacement | p. 177 |

Cost and Sample Sizes | p. 177 |

Derivations for Multistage Designs | p. 179 |

Unbiased Estimator | p. 179 |

Ratio Estimator | p. 181 |

Probability-Proportional-to-Size Sampling | p. 181 |

More Than Two Stages | p. 181 |

Exercises | p. 182 |

Double or Two-Phase Sampling | p. 183 |

Ratio Estimation with Double Sampling | p. 184 |

Allocation in Double Sampling for Ratio Estimation | p. 186 |

Double Sampling for Stratification | p. 186 |

Derivations for Double Sampling | p. 188 |

Approximate Mean and Variance: Ratio Estimation | p. 188 |

Optimum Allocation for Ratio Estimation | p. 189 |

Expected Value and Variance: Stratification | p. 189 |

Nonsampling Errors and Double Sampling | p. 190 |

Nonresponse, Selection Bias, or Volunteer Bias | p. 191 |

Double Sampling to Adjust for Nonresponse: Callbacks | p. 192 |

Response Modeling and Nonresponse Adjustments | p. 193 |

Computing Notes | p. 195 |

Exercises | p. 197 |

Methods For Elusive And Hard-To-Detect Populations | p. 199 |

Network Sampling and Link-Tracing Designs | p. 201 |

Estimation of the Population Total or Mean | p. 202 |

Multiplicity Estimator | p. 202 |

Horvitz-Thompson Estimator | p. 204 |

Derivations and Comments | p. 207 |

Stratification in Network Sampling | p. 208 |

Other Link-Tracing Designs | p. 210 |

Computing Notes | p. 212 |

Exercises | p. 213 |

Detectability and Sampling | p. 215 |

Constant Detectability over a Region | p. 215 |

Estimating Detectability | p. 217 |

Effect of Estimated Detectability | p. 218 |

Detectability with Simple Random Sampling | p. 219 |

Estimated Detectability and Simple Random Sampling | p. 220 |

Sampling with Replacement | p. 222 |

Derivations | p. 222 |

Unequal Probability Sampling of Groups with Unequal Detection Probabilities | p. 224 |

Derivations | p. 225 |

Exercises | p. 227 |

Line and Point Transects | p. 229 |

Density Estimation Methods for Line Transects | p. 230 |

Narrow-Strip Method | p. 230 |

Smooth-by-Eye Method | p. 233 |

Parametric Methods | p. 234 |

Nonparametric Methods | p. 237 |

Estimating f (0) by the Kernel Method | p. 237 |

Fourier Series Method | p. 239 |

Designs for Selecting Transects | p. 240 |

Random Sample of Transects | p. 240 |

Unbiased Estimator | p. 241 |

Ratio Estimator | p. 243 |

Systematic Selection of Transects | p. 244 |

Selection with Probability Proportional to Length | p. 244 |

Note on Estimation of Variance for the Kernel Method | p. 246 |

Some Underlying Ideas about Line Transects | p. 247 |

Line Transects and Detectability Functions | p. 247 |

Single Transect | p. 249 |

Average Detectability | p. 249 |

Random Transect | p. 250 |

Average Detectability and Effective Area | p. 251 |

Effect of Estimating Detectability | p. 252 |

Probability Density Function of an Observed Distance | p. 253 |

Detectability Imperfect on the Line or Dependent on Size | p. 255 |

Estimation Using Individual Detectabilities | p. 255 |

Estimation of Individual Detectabilities | p. 256 |

Detectability Functions other than Line Transects | p. 257 |

Variable Circular Plots or Point Transects | p. 259 |

Exercise | p. 260 |

Capture-Recapture Sampling | p. 263 |

Single Recapture | p. 264 |

Models for Simple Capture-Recapture | p. 266 |

Sampling Design in Capture-Recapture: Ratio Variance Estimator | p. 267 |

Random Sampling with Replacement of Detectability Units | p. 269 |

Random Sampling without Replacement | p. 270 |

Estimating Detectability with Capture-Recapture Methods | p. 271 |

Multiple Releases | p. 272 |

More Elaborate Models | p. 273 |

Exercise | p. 273 |

Line-Intercept Sampling | p. 275 |

Random Sample of Lines: Fixed Direction | p. 275 |

Lines of Random Position and Direction | p. 280 |

Exercises | p. 282 |

Spatial Sampling | p. 283 |

Spatial Prediction or Kriging | p. 285 |

Spatial Covariance Function | p. 286 |

Linear Prediction (Kriging) | p. 286 |

Variogram | p. 289 |

Predicting the Value over a Region | p. 291 |

Derivations and Comments | p. 292 |

Computing Notes | p. 296 |

Exercise | p. 299 |

Spatial Designs | p. 301 |

Design for Local Prediction | p. 302 |

Design for Prediction of Mean of Region | p. 302 |

Plot Shapes and Observational Methods | p. 305 |

Observations from Plots | p. 305 |

Observations from Detectability Units | p. 307 |

Comparisons of Plot Shapes and Detectability Methods | p. 308 |

Adaptive Sampling | p. 313 |

Adaptive Sampling Designs | p. 315 |

Adaptive and Conventional Designs and Estimators | p. 315 |

Brief Survey of Adaptive Sampling | p. 316 |

Adaptive Cluster Sampling | p. 319 |

Designs | p. 321 |

Initial Simple Random Sample without Replacement | p. 322 |

Initial Random Sample with Replacement | p. 323 |

Estimators | p. 323 |

Initial Sample Mean | p. 323 |

Estimation Using Draw-by-Draw Intersections | p. 323 |

Estimation Using Initial Intersection Probabilities | p. 325 |

When Adaptive Cluster Sampling Is Better than Simple Random Sampling | p. 327 |

Expected Sample Size, Cost, and Yield | p. 328 |

Comparative Efficiencies of Adaptive and Conventional Sampling | p. 328 |

Further Improvement of Estimators | p. 330 |

Derivations | p. 333 |

Data for Examples and Figures | p. 336 |

Exercises | p. 337 |

Systematic and Strip Adaptive Cluster Sampling | p. 339 |

Designs | p. 341 |

Estimators | p. 343 |

Initial Sample Mean | p. 343 |

Estimator Based on Partial Selection Probabilities | p. 344 |

Estimator Based on Partial Inclusion Probabilities | p. 345 |

Calculations for Adaptive Cluster Sampling Strategies | p. 347 |

Comparisons with Conventional Systematic and Cluster Sampling | p. 349 |

Derivations | p. 350 |

Example Data | p. 352 |

Exercises | p. 352 |

Stratified Adaptive Cluster Sampling | p. 353 |

Designs | p. 353 |

Estimators | p. 356 |

Estimators Using Expected Numbers of Initial Intersections | p. 357 |

Estimator Using Initial Intersection Probabilities | p. 359 |

Comparisons with Conventional Stratified Sampling | p. 362 |

Further Improvement of Estimators | p. 364 |

Example Data | p. 367 |

Exercises | p. 367 |

Answers to Selected Exercises | p. 369 |

References | p. 375 |

Author Index | p. 395 |

Subject Index | p. 399 |

Table of Contents provided by Publisher. All Rights Reserved. |