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------------------Description-------------------- 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...
------------------Description-------------------- 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. ---------------------Features--------------------- Communicates the development of essential aspects of theory and methods Provides an up-to-date treatment of both classical and modern sampling design and estimation methods along with sampling methods for hard-to-detect populations Covers all aspects of obtaining, interpreting, and using sample data Aids researchers in pursuing further studies in areas of specific interest by bringing together widely scattered materials Includes many techniques not covered adequately in most books ---------------------Contents--------------------- 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
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