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Chapman and Hall/CRC
280 pages
Starting from the preliminaries and ending with live examples, Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation. The author lucidly develops and presents numerous approaches. He details recent developments and explores fresh and unseen problems, hitting upon possible solutions.
The text covers current research output in a student-friendly manner with attractive illustrations. It introduces sampling and discusses how to select a sample for which a selection-probability is specified to prescribe its performance characteristics. The author then explains how to examine samples with varying probabilities to derive profits. He then examines how to use partial segments to make reasonable guesses about a sample’s behavior and assess the elements of discrepancies.
Including case studies, exercises, and solutions, the book highlights special survey techniques needed to capture trustworthy data and put it to intelligent use. It then discusses the model-assisted approach and network sampling, before moving on to speculating about random processes. The author draws on his extensive teaching experience to create a textbook that gives your students a thorough grounding in the technologies of survey sampling and modeling and also provides you with the tools to teach them.
"… recommended to mathematicians and statisticians seeking an in-depth understanding in methodology …"
—Iris Burkholder, Zentralblatt MATH 1296
Exposure to Sampling
Abstract
Introduction
Concepts of Population, Sample, and Sampling
Initial Ramifications
Abstract
Introduction
Sampling Design, Sampling Scheme
Random Numbers and Their Uses in Simple RandomSampling (SRS)
Drawing Simple Random Samples with and withoutReplacement
Estimation of Mean, Total, Ratio of Totals/Means:Variance and Variance Estimation
Determination of Sample Sizes
A.2 Appendix to Chapter 2
A.More on Equal Probability Sampling
A.Horvitz-Thompson Estimator
A.Sufficiency
A.Likelihood
A.Non-Existence Theorem
More Intricacies
Abstract
Introduction
Unequal Probability Sampling Strategies
PPS Sampling
Exploring Improved Ways
Abstract
Introduction
Stratified Sampling
Cluster Sampling
Multi-Stage Sampling
Multi-Phase Sampling: Ratio and RegressionEstimation
viiviii ContentsControlled Sampling
Modeling
Introduction
Super-Population Modeling
Prediction Approach
Model-Assisted Approach
Bayesian Methods
Spatial Smoothing
Sampling on Successive Occasions: Panel Rotation
Non-Response and Not-at-Homes
Weighting Adjustments and Imputation
5.10 Time Series Approach in Repeated Sampling
Stigmatizing Issues
Abstract
Introduction
Early Growth of RR and the Current Status
Optional Randomized Response Techniques
Indirect Questioning
Developing Small Domain Statistics
Abstract
Introduction
Some Details
Network and Adaptive Procedures
Abstract
Introduction
Estimation by Network Sampling and Estimationby Adaptive Sampling
Constraining Network Sampling and ConstrainingAdaptive Sampling
Analytical Methods
Abstract
Analytical Surveys: Contingency Tables
A.1 Reviews and Further Openings
A.2 Case Studies
A.3 Exercises and Solutions Supplementaries
References
Author Index
Subject Index
