Finite Population Sampling and Inference by Richard Valliant

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Summary

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 on this model-based approach are scattered in disparate areas of the statistical literature.

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Finite Population Sampling and Inference by Richard Valliant

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 on this model-based approach are scattered in disparate areas of the statistical literature.
"Valliant..is joined...to dispel the perception of dichotomy between mainstream statistics...and survey sampling..." (SciTech Book News, Vol. 24, No. 4, December 2000)
"The vast majority of the book is devoted to prediction of a population mean or total, and as such it forms a cohesive and comprehensive treatment of the subject." (Mathematical Reviews, Issue 2001j)
"A highly recommended book which is an essential read for all research workers in this area." (Short Book Reviews - Publication of the Int. Statistical Institute, December 2001)
"This book is a welcome addition to the subject of survey sampling." (Zentralblatt MATH, Vol. 964, 2001/14)
RICHARD VALLIANT, PhD, is Associate Director at Westat, Rockville, Maryland.
ALAN H. DORFMAN, PhD, is Senior Mathematical Statistician for the Bureau of Labor Statistics, Washington, D.C.
RICHARD M. ROYALL, PhD, is Professor of Biostatistics, Johns Hopkins University, Baltimore, Maryland.
SKU Unavailable
ISBN 13 9780471293415
ISBN 10 0471293415
Title Finite Population Sampling and Inference
Author Richard Valliant
Series Wiley Series In Survey Methodology
Condition Unavailable
Binding Type Hardback
Publisher John Wiley & Sons Inc
Year published 2000-10-09
Number of pages 536
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.