Missing Data and Small-Area Estimation

From the reviews: "...Longford offers a lucid account of these challenges in the context of sample surveys and provides potential solutions. ...Ultimately, this book serves as an excellent reference source to guide and improve statistical practice in survey settings exhibiting these problems." Psychometrika, Vol. 72, No. 1, March 2007 "I am convinced this book will be useful to practitioners...[and a] valuable resource for future research in this field." Jan Kordos in Statistics in Transition, Vol. 7, No. 5, June 2006 "To sum up, I think this is an excellent book and it thoroughly covers methods to deal with incomplete data problems and small-area estimation. It is a useful and suitable book for survey statisticians, as well as for researchers and graduate students interested on sampling designs." Ramon Cleries Soler in Statistics and Operations Research Transactions, Vol. 30, No. 1, January-June 2006 "This book develops methods for two key problems in the analysis of large-scale surveys dealing with incomplete data and making inferences about sparsely represented subdomains. A strength of the presentation is the chapters on case studies, one for each problem. Whenever possible, turning to examples and illustrations is preferred to theoretical arguments. The book is suitable for graduate students and researchers ." (T. Postelnicu, Zentralblatt MATH, Vol. 1092 (18), 2006) "The book contains an array of topics related to missing data, small-area estimation and combining estimators. The target audiences are graduate students and researchers . The main strength of this book is the presentation of case studies and each chapter offers a reasonable number of exercises. Overall, it is well written book, which make a pleasant reading, indeed and I recommend it survey statisticians and those readers interested in the field of missing data and small area estimation." (S. E. Ahmed, Technometrics, Vol. 49 (3), August, 2007) "...[T]this is an excellent book and it thoroughly covers methods to deal with incomplete data problems and small-area estimation. It is a useful and suitable book for survey statisticians, as well as for researchers and graduate students interested in sampling designs." (Ramon Cleiries Soler, SORT, Journal of the Catalon Statistical Institute, June 2006)

Missing data.- Prologue.- Describing incompleteness.- Single imputation and related methods.- Multiple imputation.- Case studies.- Small-area estimation.- Models for small areas.- Using auxiliary information.- Using small-area estimators.- Case studies.- Combining estimators.- Model selection.