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Complex Surveys - Analysis of Categorical Data (Hardcover, 1st ed. 2016)
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Complex Surveys - Analysis of Categorical Data (Hardcover, 1st ed. 2016)
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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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