Covers a new but essential development in the field of population sampling, namely inference in finite sampling. Offers some important topics not found in other texts on sampling such as the superpopulation approach and randomized response, nonresponse and resampling techniques.
Complete coverage of the prediction approach to survey sampling in a single resource Prediction theory has been extremely influential in survey sampling for nearly three decades, yet research findings...
Basic model of sampling from a population with identifiable units; Inference under the fixed population model: the concepts of sufficiency and likelihood; inference under the fixed population model: criteria for...
In addition, the book includes real examples, applications, and a large set of exercises with solutions. The book begins with a look at the history of survey sampling.
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Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples.
Lastly the book reviews two important tools of making inference, -Model Calibration approach and Empirical Likelihood based approach. Post-stratification is another aspect which requires considerable attention.
Basic ideas and concepts; Methods of sampling; Methods of estimation.
All of the essays in this book have been reviewed by many critics. This volume can be used as a reference book for postgraduate students in economics, social sciences, medical and biological sciences, and statistics.
This book aims to provide an overview of some adaptive techniques used in estimating parameters for finite populations where the sampling at any stage depends on the sampling information obtained to date.
The three parts of this book on survey methodology combine an introduction to basic sampling theory, engaging presentation of topics that reflect current research trends, and informed discussion of the problems commonly encountered in ...