| Preface |
| Preface to the Second Edition |
| Preface to the First Edition |
| Introduction / 1： |
| Basic Ideas of Sampling and Estimation / 1.1： |
| Sampling Units / 1.2： |
| Sampling and Nonsampling Errors / 1.3： |
| Models in Sampling / 1.4： |
| Adaptive and Nonadaptive Designs / 1.5： |
| Some Sampling History / 1.6： |
| Basic Sampling / Part I： |
| Simple Random Sampling / 2： |
| Selecting a Simple Random Sample / 2.1： |
| Estimating the Population Mean / 2.2： |
| Estimating the Population Total / 2.3： |
| Some Underlying Ideas / 2.4： |
| Random Sampling with Replacement / 2.5： |
| Derivations for Random Sampling / 2.6： |
| Model-Based Approach to Sampling / 2.7： |
| Computing Notes / 2.8： |
| Entering Data in R |
| Sample Estimates |
| Simulation |
| Further Comments on the Use of Simulation |
| Exercises |
| Confidence Intervals / 3： |
| Confidence Interval for the Population Mean or Total / 3.1： |
| Finite-Population Central Limit Theorem / 3.2： |
| Sampling Distributions / 3.3： |
| Confidence Interval Computation / 3.4： |
| Simulations Illustrating the Approximate Normality of a Sampling Distribution with Small n and N |
| Daily Precipitation Data |
| Sample Size / 4： |
| Sample Size for Estimating a Population Mean / 4.1： |
| Sample Size for Estimating a Population Total / 4.2： |
| Sample Size for Relative Precision / 4.3： |
| Estimating Proportions, Ratios, and Subpopulation Means / 5： |
| Estimating a Population Proportion / 5.1： |
| Confidence Interval for a Proportion / 5.2： |
| Sample Size for Estimating a Proportion / 5.3： |
| Sample Size for Estimating Several Proportions Simultaneously / 5.4： |
| Estimating a Ratio / 5.5： |
| Estimating a Mean, Total, or Proportion of a Subpopulation / 5.6： |
| Estimating a Subpopulation Mean |
| Estimating a Proportion for a Subpopulation |
| Estimating a Subpopulation Total |
| Unequal Probability Sampling / 6： |
| Sampling with Replacement: The Hansen-Hurwitz Estimator / 6.1： |
| Any Design: The Horvitz-Thompson Estimator / 6.2： |
| Generalized Unequal-Probability Estimator / 6.3： |
| Small Population Example / 6.4： |
| Derivations and Comments / 6.5： |
| Writing an R Function to Simulate a Sampling Strategy / 6.6： |
| Comparing Sampling Strategies |
| Making The Best Use Of Survey Data / Part II： |
| Auxiliary Data and Ratio Estimation / 7： |
| Ratio Estimator / 7.1： |
| Small Population Illustrating Bias / 7.2： |
| Derivations and Approximations for the Ratio Estimator / 7.3： |
| Finite-Population Central Limit Theorem for the Ratio Estimator / 7.4： |
| Ratio Estimation with Unequal Probability Designs / 7.5： |
| Models in Ratio Estimation / 7.6： |
| Types of Estimators for a Ratio |
| Design Implications of Ratio Models / 7.7： |
| Regression Estimation / 7.8： |
| Linear Regression Estimator / 8.1： |
| Regression Estimation with Unequal Probability Designs / 8.2： |
| Regression Model / 8.3： |
| Multiple Regression Models / 8.4： |
| Design Implications of Regression Models / 8.5： |
| The Sufficient Statistic in Sampling / 9： |
| The Set of Distinct, Labeled Observations / 9.1： |
| Estimation in Random Sampling with Replacement / 9.2： |
| Estimation in Probability-Proportional-to-Size Sampling / 9.3： |
| Comments on the Improved Estimates / 9.4： |
| Design and Model / 10： |
| Uses of Design and Model in Sampling / 10.1： |
| Connections between the Design and Model Approaches / 10.2： |
| Some Comments / 10.3： |
| Likelihood Function in Sampling / 10.4： |
| Some Useful Designs / Part III： |
| Stratified Sampling / 11： |
| With Any Stratified Design / 11.1： |
| With Stratified Random Sampling |
| The Stratification Principle / 11.2： |
| Allocation in Stratified Random Sampling / 11.5： |
| Poststratification / 11.6： |
| Population Model for a Stratified Population / 11.7： |
| Derivations for Stratified Sampling / 11.8： |
| Optimum Allocation |
| Poststratification Variance |
| Cluster and Systematic Sampling / 11.9： |
| Primary Units Selected by Simple Random Sampling / 12.1： |
| Unbiased Estimator |
| Primary Units Selected with Probabilities Proportional to Size / 12.2： |
| Hansen-Hurwitz (PPS) Estimator |
| Horvitz-Thompson Estimator |
| The Basic Principle / 12.3： |
| Single Systematic Sample / 12.4： |
| Variance and Cost in Cluster and Systematic Sampling / 12.5： |
| Multistage Designs / 12.6： |
| Simple Random Sampling at Each Stage / 13.1： |
| Primary Units Selected with Probability Proportional to Size / 13.2： |
| Any Multistage Design with Replacement / 13.3： |
| Cost and Sample Sizes / 13.4： |
| Derivations for Multistage Designs / 13.5： |
| Probability-Proportional-to-Size Sampling |
| More Than Two Stages |
| Double or Two-Phase Sampling / 14： |
| Ratio Estimation with Double Sampling / 14.1： |
| Allocation in Double Sampling for Ratio Estimation / 14.2： |
| Double Sampling for Stratification / 14.3： |
| Derivations for Double Sampling / 14.4： |
| Approximate Mean and Variance: Ratio Estimation |
| Optimum Allocation for Ratio Estimation |
| Expected Value and Variance: Stratification |
| Nonsampling Errors and Double Sampling / 14.5： |
| Nonresponse, Selection Bias, or Volunteer Bias |
| Double Sampling to Adjust for Nonresponse: Callbacks |
| Response Modeling and Nonresponse Adjustments |
| Methods For Elusive And Hard-To-Detect Populations / 14.6： |
| Network Sampling and Link-Tracing Designs / 15： |
| Estimation of the Population Total or Mean / 15.1： |
| Multiplicity Estimator |
| Stratification in Network Sampling / 15.2： |
| Other Link-Tracing Designs / 15.4： |
| Detectability and Sampling / 15.5： |
| Constant Detectability over a Region / 16.1： |
| Estimating Detectability / 16.2： |
| Effect of Estimated Detectability / 16.3： |
| Detectability with Simple Random Sampling / 16.4： |
| Estimated Detectability and Simple Random Sampling / 16.5： |
| Sampling with Replacement / 16.6： |
| Derivations / 16.7： |
| Unequal Probability Sampling of Groups with Unequal Detection Probabilities / 16.8： |
| Line and Point Transects / 16.9： |
| Density Estimation Methods for Line Transects / 17.1： |
| Narrow-Strip Method / 17.2： |
| Smooth-by-Eye Method / 17.3： |
| Parametric Methods / 17.4： |
| Nonparametric Methods / 17.5： |
| Estimating f (0) by the Kernel Method |
| Fourier Series Method |
| Designs for Selecting Transects / 17.6： |
| Random Sample of Transects / 17.7： |
| Systematic Selection of Transects / 17.8： |
| Selection with Probability Proportional to Length / 17.9： |
| Note on Estimation of Variance for the Kernel Method / 17.10： |
| Some Underlying Ideas about Line Transects / 17.11： |
| Line Transects and Detectability Functions |
| Single Transect |
| Average Detectability |
| Random Transect |
| Average Detectability and Effective Area |
| Effect of Estimating Detectability |
| Probability Density Function of an Observed Distance |
| Detectability Imperfect on the Line or Dependent on Size / 17.12： |
| Estimation Using Individual Detectabilities / 17.13： |
| Estimation of Individual Detectabilities |
| Detectability Functions other than Line Transects / 17.14： |
| Variable Circular Plots or Point Transects / 17.15： |
| Exercise |
| Capture-Recapture Sampling / 18： |
| Single Recapture / 18.1： |
| Models for Simple Capture-Recapture / 18.2： |
| Sampling Design in Capture-Recapture: Ratio Variance Estimator / 18.3： |
| Random Sampling with Replacement of Detectability Units |
| Random Sampling without Replacement |
| Estimating Detectability with Capture-Recapture Methods / 18.4： |
| Multiple Releases / 18.5： |
| More Elaborate Models / 18.6： |
| Line-Intercept Sampling / 19： |
| Random Sample of Lines: Fixed Direction / 19.1： |
| Lines of Random Position and Direction / 19.2： |
| Spatial Sampling / Part V： |
| Spatial Prediction or Kriging / 20： |
| Spatial Covariance Function / 20.1： |
| Linear Prediction (Kriging) / 20.2： |
| Variogram / 20.3： |
| Predicting the Value over a Region / 20.4： |
| Spatial Designs / 20.5： |
| Design for Local Prediction / 21.1： |
| Design for Prediction of Mean of Region / 21.2： |
| Plot Shapes and Observational Methods / 22： |
| Observations from Plots / 22.1： |
| Observations from Detectability Units / 22.2： |
| Comparisons of Plot Shapes and Detectability Methods / 22.3： |
| Adaptive Sampling / Part VI： |
| Adaptive Sampling Designs / 23： |
| Adaptive and Conventional Designs and Estimators / 23.1： |
| Brief Survey of Adaptive Sampling / 23.2： |
| Adaptive Cluster Sampling / 24： |
| Designs / 24.1： |
| Initial Simple Random Sample without Replacement |
| Initial Random Sample with Replacement |
| Estimators / 24.2： |
| Initial Sample Mean |
| Estimation Using Draw-by-Draw Intersections |
| Estimation Using Initial Intersection Probabilities |
| When Adaptive Cluster Sampling Is Better than Simple Random Sampling / 24.3： |
| Expected Sample Size, Cost, and Yield / 24.4： |
| Comparative Efficiencies of Adaptive and Conventional Sampling / 24.5： |
| Further Improvement of Estimators / 24.6： |
| Data for Examples and Figures / 24.7： |
| Systematic and Strip Adaptive Cluster Sampling / 25： |
| Estimator Based on Partial Selection Probabilities / 25.1： |
| Estimator Based on Partial Inclusion Probabilities |
| Calculations for Adaptive Cluster Sampling Strategies / 25.3： |
| Comparisons with Conventional Systematic and Cluster Sampling / 25.4： |
| Example Data / 25.5： |
| Stratified Adaptive Cluster Sampling / 26： |
| Estimators Using Expected Numbers of Initial Intersections / 26.1： |
| Estimator Using Initial Intersection Probabilities |
| Comparisons with Conventional Stratified Sampling / 26.3： |
| Answers to Selected Exercises / 26.4： |
| References |
| Author Index |
| Subject Index |
図書
