Chaudhuri / Stenger Survey Sampling

Theory and Methods, Second Edition
2. Auflage 2010
ISBN: 978-1-4200-2863-8
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 416 Seiten

Reihe: Statistics: A Series of Textbooks and Monographs

Since publication of the first edition in 1992, the field of survey sampling has grown considerably. This new edition of Survey Sampling: Theory and Methods has been updated to include the latest research and the newest methods. The authors have undertaken the daunting task of surveying the sampling literature of the past decade to provide an outstanding research reference. Starting with the unified theory, the authors explain in the clearest of terms the subsequent developments. In fact, even the most modern innovations of survey sampling, both methodological and theoretical, have found a place in this concise volume.

See what's new in the Second Edition:

- Descriptions of new developments

- A wider range of approaches to common problems

- Increased coverage of methods that combine design and model-based approaches, adjusting for sample errors

Covering the current state of development of essential aspects of theory and methods of survey sampling, the authors have taken great care to avoid being dogmatic and eschew taking sides in their presentation. They have created tool for graduate and advanced level students and a reference for researchers and practitioners that goes beyond the coverage found in most textbooks.

Zielgruppe

Graduate and advanced level students, researchers, and practitioners

Autoren/Hrsg.

Chaudhuri, Arijit

Stenger, Horst

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

Foreword
Preface to the Second Edition
Preface to the First Edition

ESTIMATION IN FINITE POPULATIONS: A UNIFIED THEORY
Introduction
Elementary Definitions
Design-Based Inference
Sampling Schemes
Controlled Sampling

STRATEGIES DEPENDING ON AUXILIARY VARIABLES
Representative Strategies
Examples of Representative Strategies
Estimation of the Mean Square Error
Estimation of Mp(t ) for Specific Strategies
Calibration

CHOOSING GOOD SAMPLING STRATEGIES
Fixed Population Approach
Superpopulation Approach
Estimating Equation Approach
Minimax Approach

PREDICTORS
Model-Dependent Estimation
Prior Distribution-Based Approach

ASYMPTOTIC ASPECTS IN SURVEY SAMPLING
Increasing Populations
Consistency, Asymptotic Unbiasedness
Brewer's Asymptotic Approach
Moment-Type Estimators
Asymptotic Normality and Confidence Intervals

APPLICATIONS OF ASYMPTOTICS
A Model-Assisted Approach
Asymptotic Minimaxity

DESIGN- AND MODEL-BASED VARIANCE ESTIMATION
Ratio Estimator
Regression Estimator
HT Estimator
GREG Predictor
Systematic Sampling

MULTISTAGE, MULTIPHASE, AND REPETITIVE SAMPLING
Variance Estimators Due to Raj and Rao in Multistage Sampling: More Recent Developments
Double Sampling with Equal and Varying Probabilities: Design-Unbiased and Regression Estimators
Sampling on Successive Occasions with Varying Probabilities

RESAMPLING AND VARIANCE ESTIMATION IN COMPLEX SURVEYS
Linearization
Jackknife
Interpenetrating Network of Subsampling and Replicated Sampling
Balanced Repeated Replication
Bootstrap

SAMPLING FROM INADEQUATE FRAMES
Domain Estimation
Poststratification
Estimation from Multiple Frames
Small Area Estimation
Conditional Inference

ANALYTIC STUDIES OF SURVEY DATA
Design Effects on Categorical Data Analysis
Regression Analysis from Complex Survey Data

RANDOMIZED RESPONSE
SRSWR for Qualitative and Quantitative Data
A General Approach

INCOMPLETE DATA
Nonsampling Errors
Nonresponse
Callbacks
Weight Adjustments
Use of Superpopulation Models
Adaptive Sampling and Network Sampling
Imputation

EPILOGUE
Appendix
References
List of Abbreviations, Special Notations,
and Symbols
Author Index
Subject Index