Complex Surveys: Analysis of Categorical Data

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Springer, May 21, 2016 - Mathematics - 248 pages
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.
 

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Contents

1 Preliminaries
1
2 The Design Effects and Misspecification Effects
27
3 Some Classical Models in Categorical Data Analysis
67
4 Analysis of Categorical Data Under a Full Model
97
5 Analysis of Categorical Data Under LogLinear Models
135
6 Analysis of Categorical Data Under Logistic Regression Model
157
7 Analysis in the Presence of Classification Errors
179
8 Approximate MLE from Survey Data
195
Appendix A Asymptotic Properties of Multinomial Distribution
223
References
241
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About the author (2016)

PARIMAL MUKHOPADHYAY is a former professor of statistics at the Indian Statistical Institute, Kolkata, India. He received his PhD degree in statistics from the University of Calcutta in 1977. He also served as a faculty member at the University of Ife, Nigeria, Moi University, Kenya, University of South Pacific, Fiji Islands and held visiting positions at the University of Montreal, University of Windsor, Stockholm University and the University of Western Australia. He has written more than seventy five research papers in survey sampling, some co-authored and eleven books on statistics. He is a member of the Institute of Mathematical Statistics and elected member of the International Statistical Institute.

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