Complex surveys : analysis of categorical data /

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Bibliographic Details
Author / Creator:Mukhopadhyay, Parimal, author.
Imprint:Sinagpore : Springer, 2016.
Description:1 online resource (xii, 248 pages)
Language:English
Subject:Sampling (Statistics)
Mathematical statistics.
Probability & statistics.
Social research & statistics.
MATHEMATICS -- Applied.
MATHEMATICS -- Probability & Statistics -- General.
Mathematical statistics.
Sampling (Statistics)
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11255992
Hidden Bibliographic Details
ISBN:9789811008719
981100871X
9811008701
9789811008702
9789811008702
Digital file characteristics:text file
PDF
Notes:Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed May 25, 2016).
Summary:The primary objective of this book is to study some of the research topics in the area of analysis of complex surveys which have not been covered in any book yet. It discusses the analysis of categorical data using three models: a full model, a log-linear model and a logistic regression model. It is a valuable resource for survey statisticians and practitioners in the field of sociology, biology, economics, psychology and other areas who have to use these procedures in their day-to-day work. It is also useful for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. The importance of sample surveys today cannot be overstated. From voters' behaviour to fields such as industry, agriculture, economics, sociology, psychology, investigators generally resort to survey sampling to obtain an assessment of the behaviour of the population they are interested in. Many large-scale sample surveys collect data using complex survey designs like multistage stratified cluster designs. The observations using these complex designs are not independently and identically distributed - an assumption on which the classical procedures of inference are based. This means that if classical tests are used for the analysis of such data, the inferences obtained will be inconsistent and often invalid. For this reason, many modified test procedures have been developed for this purpose over the last few decades.
Other form:Print version: Mukhopadhyay, Parimal. Complex surveys : analysis of categorical data. Sinagpore, [Singapore] : Springer, ©2016 xv, 248 pages 9789811008702
Standard no.:10.1007/978-981-10-0871-9