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CONTENTS Series Editor?s Introduction Acknowledgments 1. Introduction 2. Sample Design and Survey Data Types of Sampling The Nature of Survey Data A Different View of Survey Data* 3. Complexity of Analyzing Survey Data Adjusting for Differential Representation: The Weight Developing the Weight by Poststratification Adjusting the Weight in a Followup Survey Assessing the Loss or Gain in Precision: The Design Effect The Use of Sample Weights for Survey Data Analysis* 4. Strategies for Variance Estimation Replicated Sampling: A General Approach Balanced Repeated Replication Jackknife Repeated Replication The Bootstrap Method The Taylor Series Method (Linearization) 5. Preparing for Survey Data Analysis Data Requirements for Survey Analysis Importance of Preliminary Analysis Choices of the Method for Variance Estimation Available Computing Resources Creating Replicate Weights Searching for Appropriate Models for Survey Data Analysis* 6. 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 Analysis* 7. Concluding Remarks Notes References About the Authors
Library of Congress Subject Headings for this publication:
Mathematical statistics.
Social surveys -- Statistical methods.