Sampling：Design and Analysis

by Sharon L. Lohr, 2nd edition Arizona State University in English C HA P T E R 1 Introduction 1 1.1 A Sample Controversy 1 1.2 Requirements of a Good Sample 3 1.3 Selection Bias 5 1.4 Measurement Error 9 1.5 Questionnaire Design 11 1.6 Sampling and Nonsampling Errors 16 1.7 Exercises 19 C HA P T E R 2 Simple Probability Samples 25 2.1 Types of Probability Samples 25 2.2 Framework for Probability Sampling 28 2.3 Simple Random Sampling 33 2.4 SamplingWeights 39 2.5 Confidence Intervals 40 2.6 Sample Size Estimation 46 2.7 Systematic Sampling 50 2.8 Randomization Theory Results for Simple Random Sampling 51 2.9 A Prediction Approach for Simple Random Sampling 54 2.10 When Should a Simple Random Sample Be Used? 58 2.11 Chapter Summary 59 2.12 Exercises 61 C HA P T E R 3 Stratified Sampling 73 3.1 What Is Stratified Sampling? 73 3.2 Theory of Stratified Sampling 77 3.3 SamplingWeights in Stratified Random Sampling 82 3.4 Allocating Observations to Strata 85 3.5 Defining Strata 91 3.6 Model-Based Inference for Stratified Sampling 95 3.7 Quota Sampling 96 3.8 Chapter Summary 99 3.9 Exercises 101 C HA P T E R 4 Ratio and Regression Estimation 117 4.1 Ratio Estimation in a Simple Random Sample 118 4.2 Estimation in Domains 133 4.3 Regression Estimation in Simple Random Sampling 138 4.4 Poststratification 142 4.5 Ratio Estimation with Stratified Samples 144 4.6 Model-Based Theory for Ratio and Regression Estimation 146 4.7 Chapter Summary 154 4.8 Exercises 155 C HA P T E R 5 Cluster Sampling with Equal Probabilities 165 5.1 Notation for Cluster Sampling 168 5.2 One-Stage Cluster Sampling 170 5.3 Two-Stage Cluster Sampling 182 5.4 Designing a Cluster Sample 191 5.5 Systematic Sampling 196 5.6 Model-Based Inference in Cluster Sampling 200 5.7 Chapter Summary 205 5.8 Exercises 207 etc