Description
Book SynopsisComplete 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.
Trade Review"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)
Table of ContentsIntroduction to Prediction Theory.
Prediction Theory Under the General Linear Model.
Bias-Robustness.
Robustness and Efficiency.
Variance Estimation.
Stratified Populations.
Models with Qualitative Auxiliaries.
Clustered Populations.
Robust Variance Estimation in Two-Stage Cluster Sampling.
Alternative Variance Estimation Methods.
Special Topics and Open Questions.
Appendices.
Bibliography.
Answers to Select Exercises.
Indexes.
