Sampling /
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Author / Creator: | Thompson, Steven K., 1945- |
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Edition: | 2nd ed. |
Imprint: | New York : Wiley, c2002. |
Description: | xvii, 367 p. : ill. ; 24 cm. |
Language: | English |
Series: | Wiley series in probability and statistics |
Subject: | Sampling (Statistics) Sampling (Statistics) |
Format: | Print Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/4663813 |
Table of Contents:
- Preface to the Second Edition
- Preface to the First Edition
- 1.. Introduction
- 1.1. Basic Ideas of Sampling and Estimation
- 1.2. Sampling Units
- 1.3. Sampling and Nonsampling Errors
- 1.4. Models in Sampling
- 1.5. Adaptive and Nonadaptive Designs
- 1.6. Some Sampling History
- Part I. Basic Sampling
- 2.. Simple Random Sampling
- 2.1. Selecting a Simple Random Sample
- 2.2. Estimating the Population Mean
- 2.3. Estimating the Population Total
- 2.4. Some Underlying Ideas
- 2.5. Random Sampling with Replacement
- 2.6. Derivations for Random Sampling
- 2.7. Model-Based Approach to Sampling
- Exercises
- 3.. Confidence Intervals
- 3.1. Confidence Interval for the Population Mean or Total
- 3.2. Finite-Population Central Limit Theorem
- Exercises
- 4.. Sample Size
- 4.1. Sample Size for Estimating a Population Mean
- 4.2. Sample Size for Estimating a Population Total
- 4.3. Sample Size for Relative Precision
- Exercises
- 5.. Estimating Proportions, Ratios, and Subpopulation Means
- 5.1. Estimating a Population Proportion
- 5.2. Confidence Interval for a Proportion
- 5.3. Sample Size for Estimating a Proportion
- 5.4. Sample Size for Estimating Several Proportions Simultaneously
- 5.5. Estimating a Ratio
- 5.6. Estimating a Mean, Total, or Proportion of a Subpopulation
- Estimating a Subpopulation Mean
- Estimating a Proportion for a Subpopulation
- Estimating a Subpopulation Total
- Exercises
- 6.. Unequal Probability Sampling
- 6.1. Sampling with Replacement: The Hansen--Hurwitz Estimator
- 6.2. Any Design: The Horvitz--Thompson Estimator
- 6.3. Generalized Unequal-Probability Estimator
- 6.4. Small Population Example
- 6.5. Derivations and Comments
- Exercises
- Part II. Making the Best Use of Survey Data
- 7.. Auxiliary Data and Ratio Estimation
- 7.1. Ratio Estimator
- 7.2. Small Population Illustrating Bias
- 7.3. Derivations and Approximations for the Ratio Estimator
- 7.4. Finite-Population Central Limit Theorem for the Ratio Estimator
- 7.5. Ratio Estimation with Unequal Probability Designs
- 7.6. Models in Ratio Estimation
- Types of Estimators for a Ratio
- 7.7. Design Implications of Ratio Models
- Exercises
- 8.. Regression Estimation
- 8.1. Linear Regression Estimator
- 8.2. Regression Estimation with Unequal Probability Designs
- 8.3. Regression Model
- 8.4. Multiple Regression Models
- 8.5. Design Implications of Regression Models
- Exercises
- 9.. The Sufficient Statistic in Sampling
- 9.1. The Set of Distinct, Labeled Observations
- 9.2. Estimation in Random Sampling with Replacement
- 9.3. Estimation in Probability-Proportional-to-Size Sampling
- 9.4. Comments on the Improved Estimates
- 10.. Design and Model
- 10.1. Uses of Design and Model in Sampling
- 10.2. Connections between the Design and Model Approaches
- 10.3. Some Comments
- 10.4. Likelihood Function in Sampling
- Part III. Some Useful Designs
- 11.. Stratified Sampling
- 11.1. Estimating the Population Total
- With Any Stratified Design
- With Stratified Random Sampling
- 11.2. Estimating the Population Mean
- With Any Stratified Design
- With Stratified Random Sampling
- 11.3. Confidence Intervals
- 11.4. The Stratification Principle
- 11.5. Allocation in Stratified Random Sampling
- 11.6. Poststratification
- 11.7. Population Model for a Stratified Population
- 11.8. Derivations for Stratified Sampling
- Optimum Allocation
- Poststratification Variance
- Exercises
- 12.. Cluster and Systematic Sampling
- 12.1. Primary Units Selected by Simple Random Sampling
- Unbiased Estimator
- Ratio Estimator
- 12.2. Primary Units Selected with Probabilities Proportional to Size
- Hansen--Hurwitz (PPS) Estimator
- Horvitz--Thompson Estimator
- 12.3. The Basic Principle
- 12.4. Single Systematic Sample
- 12.5. Variance and Cost in Cluster and Systematic Sampling
- Exercises
- 13.. Multistage Designs
- 13.1. Simple Random Sampling at Each Stage
- Unbiased Estimator
- Ratio Estimator
- 13.2. Primary Units Selected with Probability Proportional to Size
- 13.3. Any Multistage Design with Replacement
- 13.4. Cost and Sample Sizes
- 13.5. Derivations for Multistage Designs
- Unbiased Estimator
- Ratio Estimator
- Probability-Proportional-to-Size Sampling
- More Than Two Stages
- Exercises
- 14.. Double or Two-Phase Sampling
- 14.1. Ratio Estimation with Double Sampling
- 14.2. Allocation in Double Sampling for Ratio Estimation
- 14.3. Double Sampling for Stratification
- 14.4. Derivations for Double Sampling
- Approximate Mean and Variance: Ratio Estimation
- Optimum Allocation for Ratio Estimation
- Expected Value and Variance: Stratification
- 14.5. Nonsampling Errors and Double Sampling
- Nonresponse, Selection Bias, or Volunteer Bias
- Double Sampling to Adjust for Nonresponse: Callbacks
- Response Modeling and Nonresponse Adjustments
- Exercises
- Part IV. Methods for Elusive and Hard-to-Detect Populations
- 15.. Network Sampling and Link-Tracing Designs
- 15.1. Estimation of the Population Total or Mean
- Multiplicity Estimator
- Horvitz--Thompson Estimator
- 15.2. Derivations and Comments
- 15.3. Stratification in Network Sampling
- 15.4. Other Link-Tracing Designs
- Exercises
- 16.. Detectability and Sampling
- 16.1. Constant Detectability over a Region
- 16.2. Estimating Detectability
- 16.3. Effect of Estimated Detectability
- 16.4. Detectability with Simple Random Sampling
- 16.5. Estimated Detectability and Simple Random Sampling
- 16.6. Sampling with Replacement
- 16.7. Derivations
- 16.8. Unequal Probability Sampling of Groups with Unequal Detection Probabilities
- 16.9. Derivations
- Exercises
- 17.. Line and Point Transects
- 17.1. Density Estimation Methods for Line Transects
- 17.2. Narrow-Strip Method
- 17.3. Smooth-by-Eye Method
- 17.4. Parametric Methods
- 17.5. Nonparametric Methods
- Estimating f(0) by the Kernel Method
- Fourier Series Method
- 17.6. Designs for Selecting Transects
- 17.7. Random Sample of Transects
- Unbiased Estimator
- Ratio Estimator
- 17.8. Systematic Selection of Transects
- 17.9. Selection with Probability Proportional to Length
- 17.10. Note on Estimation of Variance for the Kernel Method
- 17.11. Some Underlying Ideas about Line Transects
- 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
- 17.12. Detectability Imperfect on the Line or Dependent on Size
- 17.13. Estimation Using Individual Detectabilities
- Estimation of Individual Detectabilities
- 17.14. Detectability Functions Other Than Line Transects
- 17.15. Variable Circular Plots or Point Transects
- Exercise
- 18.. Capture--Recapture Sampling
- 18.1. Single Recapture
- 18.2. Models for Simple Capture--Recapture
- 18.3. Sampling Design in Capture--Recapture: Ratio Variance Estimator
- Random Sampling with Replacement of Detectability Units
- Random Sampling without Replacement
- 18.4. Estimating Detectability with Capture--Recapture Methods
- 18.5. Multiple Releases
- 18.6. More Elaborate Models
- Exercise
- 19.. Line-Intercept Sampling
- 19.1. Random Sample of Lines: Fixed Direction
- 19.2. Lines of Random Position and Direction
- Exercises
- Part V. Spatial Sampling
- 20.. Spatial Prediction or Kriging
- 20.1. Spatial Covariance Function
- 20.2. Linear Prediction (Kriging)
- 20.3. Variogram
- 20.4. Predicting the Value over a Region
- 20.5. Derivations and Comments
- Exercise
- 21.. Spatial Designs
- 21.1. Design for Local Prediction
- 21.2. Design for Prediction of Mean of Region
- 22.. Plot Shapes and Observational Methods
- 22.1. Observations from Plots
- 22.2. Observations from Detectability Units
- 22.3. Comparisons of Plot Shapes and Detectability Methods
- Part VI. Adaptive Sampling
- 23.. Adaptive Sampling Designs
- 23.1. Adaptive and Conventional Designs and Estimators
- 23.2. Brief Survey of Adaptive Sampling
- 24.. Adaptive Cluster Sampling
- 24.1. Designs
- Initial Simple Random Sample without Replacement
- Initial Random Sample with Replacement
- 24.2. Estimators
- Initial Sample Mean
- Estimation Using Draw-by-Draw Intersections
- Estimation Using Initial Intersection Probabilities
- 24.3. When Adaptive Cluster Sampling Is Better Than Simple Random Sampling
- 24.4. Expected Sample Size, Cost, and Yield
- 24.5. Comparative Efficiencies of Adaptive and Conventional Sampling
- 24.6. Further Improvement of Estimators
- 24.7. Derivations
- 24.8. Data for Examples and Figures
- Exercises
- 25.. Systematic and Strip Adaptive Cluster Sampling
- 25.1. Designs
- 25.2. Estimators
- Initial Sample Mean
- Estimator Based on Partial Selection Probabilities
- Estimator Based on Partial Inclusion Probabilities
- 25.3. Calculations for Adaptive Cluster Sampling Strategies
- 25.4. Comparisons with Conventional Systematic and Cluster Sampling
- 25.5. Derivations
- 25.6. Example Data
- Exercises
- 26.. Stratified Adaptive Cluster Sampling
- 26.1. Designs
- 26.2. Estimators
- Estimators Using Expected Numbers of Initial Intersections
- Estimator Using Initial Intersection Probabilities
- 26.3. Comparisons with Conventional Stratified Sampling
- 26.4. Further Improvement of Estimators
- 26.5. Example Data
- Exercises
- Answers to Selected Exercises
- References
- Author Index
- Subject Index