Analyzing Complex Survey Data

Informationen zum Autor Experience & Interest Teaching and research in public health (Survey design and analysis in mental health and nutrition, demographic analysis of infant mortality and reproductive health, biostatical and epidemiologic analysis of cancer registry data and environmental surveys, statistical methods in epidemiology) Klappentext 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. Zusammenfassung Examines ways to analyze surveys! and focuses on the problems of weights and design effects. This edition incorporates practice of analyzing complex survey data! introduces the analytic approach for categorical data analysis! reviews new software and provides an introduction to the model-based analysis that can be useful analyzing social surveys. Inhaltsverzeichnis 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 Follow-Up 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 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 Analyses 7. Concluding Remarks Notes References Index About the Authors ...

Autorentext

Experience & Interest
Teaching and research in public health (Survey design and analysis in mental health and nutrition, demographic analysis of infant mortality and reproductive health, biostatical and epidemiologic analysis of cancer registry data and environmental surveys, statistical methods in epidemiology)

Klappentext

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.

Zusammenfassung
Examines ways to analyze surveys, and focuses on the problems of weights and design effects. This edition incorporates practice of analyzing complex survey data, introduces the analytic approach for categorical data analysis, reviews new software and provides an introduction to the model-based analysis that can be useful analyzing social surveys.

Inhalt

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 Follow-Up 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 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 Analyses
7. Concluding Remarks
   Notes
   References
   Index
   About the Authors