Analyzing Complex Survey Data

Name: Analyzing Complex Survey Data
Price: 22.0 USD
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ISBN: 9780761930389

ISBN-10: 0761930388

ISBN-13: 9780761930389

Edition: 2nd 2006 (Revised)

Authors: Eun Sul Lee, Ronald N. Forthofer

List price: $42.00

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This book examines ways to analyze complex surveys, and focuses on the problems of weights and design effects. This new edition incorporates recent practice of analyzing complex survey data, introduces the new analytic approach for categorical data analysis (logistic regression), reviews new software and provides an introduction to the model-based analysis that can be useful analyzing well-designed, relatively small-scale social surveys.

Book details

List price: $42.00
Edition: 2nd
Copyright year: 2006
Publisher: SAGE Publications, Incorporated
Publication date: 9/22/2005
Binding: Paperback
Pages: 104
Size: 5.50" wide x 8.30" long x 0.30" tall
Weight: 0.242



Series Editor's Introduction


Acknowledgments



Introduction



Sample Design and Survey Data


Types of Sampling


The Nature of Survey Data


A Different View of Survey Data



Complexity of Analyzing Survey Data


Adjusting for Differential Representation: The Weight


Developing the Weight by Poststratification


Adjusting the Weight in a Follow-Up Survey


Assessing the Loss or Gain in Precision: The Design Effect


The Use of Sample Weights for Survey Data Analysis



Strategies for Variance Estimation


Replicated Sampling: A General Approach


Balanced Repeated Replication


Jackknife Repeated Replication


The Bootstrap Method


The Taylor Series Method (Linearization)



Preparing for Survey Data Analysis


Data Requirements for Survey Analysis


Importance of Preliminary Analysis


Choices of Method for Variance Estimation


Available Computing Resources


Creating Replicate Weights


Searching for Appropriate Models for Survey Data Analysis



Conducting Survey Data Analysis


A Strategy for Conducting Preliminary Analysis


Conducting Descriptive Analysis


Conducting Linear Regression Analysis


Conducting Contingency Table Analysis


Conducting Logistic Regression Analysis


Other Logistic Regression Models


Design-Based and Model-Based Analyses



Concluding Remarks


Notes


References


Index


About the Authors