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| Applied Survey Data Analysis: Overview | |
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| Introduction | |
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| A Brief History of Applied Survey Data Analysis | |
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| Example Data Sets and Exercises | |
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| Getting to Know the Complex Sample Design | |
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| Introduction | |
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| Classification of Sample Designs | |
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| Target Populations and Survey Populations | |
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| Simple Random Sampling: A Simple Model for Design-Based Inference | |
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| Complex Sample Design Effects | |
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| Complex Samples: Clustering and Stratification | |
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| Weighting in Analysis of Survey Data | |
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| Multistage Area Probability Sample Designs | |
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| Special Types of Sampling Plans Encountered in Surveys | |
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| Foundations and Techniques for Design-Based Estimation and Inference | |
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| Introduction | |
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| Finite Populations and Superpopulation Models | |
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| Confidence Intervals for Population Parameters | |
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| Weighted Estimation of Population Parameters | |
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| Probability Distributions and Design-Based Inference | |
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| Variance Estimation | |
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| Hypothesis Testing in Survey Data Analysis | |
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| Total Survey Error and Its Impact on Survey Estimation and Inference | |
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| Preparation for Complex Sample Survey Data Analysis | |
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| Introduction | |
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| Analysis Weights: Review by the Data User | |
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| Understanding and Checking the Sampling Error Calculation Model | |
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| Addressing Item Missing Data in Analysis Variables | |
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| Preparing to Analyze Data for Sample Subpopulations | |
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| A Final Checklist for Data Users | |
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| Descriptive Analysis for Continuous Variables | |
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| Introduction | |
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| Special Considerations in Descriptive Analysis of Complex Sample Survey Data | |
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| Simple Statistics for Univariate Continuous Distributions | |
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| Bivariate Relationships between Two Continuous Variables | |
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| Descriptive Statistics for Subpopulations | |
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| Linear Functions of Descriptive Estimates and Differences of Means | |
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| Exercises | |
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| Categorical Data Analysis | |
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| Introduction | |
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| A Framework for Analysis of Categorical Survey Data | |
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| Univariate Analysis of Categorical Data | |
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| Bivariate Analysis of Categorical Data | |
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| Analysis of Multivariate Categorical Data | |
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| Exercises | |
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| Linear Regression Models | |
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| Introduction | |
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| The Linear Regression Model | |
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| Four Steps in Linear Regression Analysis | |
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| Some Practical Considerations and Tools | |
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| Application: Modeling Diastolic Blood Pressure with the NHANES Data | |
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| Exercises | |
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| Logistic Regression and Generalized Linear Models (GLMs) for Binary Survey Variables | |
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| Introduction | |
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| GLMs for Binary Survey Responses | |
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| Building the Logistic Regression Model: Stage 1, Model Specification | |
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| Building the Logistic Regression Model: Stage 2, Estimation of Model Parameters and Standard Errors | |
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| Building the Logistic Regression Model: Stage 3, Evaluation of the Fitted Model | |
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| Building the Logistic Regression Model: Stage 4, Interpretation and Inference | |
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| Analysis Application | |
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| Comparing the Logistic, Probit, and Complementary Log-Log GLMs for Binary Dependent Variables | |
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| Exercises | |
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| GLMs for Multinomial, Ordinal, and Count Variables | |
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| Introduction | |
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| Analyzing Survey Data Using Multinomial Logit | |
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| Regression Models | |
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| Logistic Regression Models for Ordinal Survey Data | |
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| Regression Models for Count Outcomes | |
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| Exercises | |
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| Survival Analysis of Event History Survey Data | |
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| Introduction | |
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| Basic Theory of Survival Analysis | |
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| (Nonparametric) Kaplan-Meier Estimation of the Survivor Function | |
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| Cox Proportional Hazards Model | |
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| Discrete Time Survival Models | |
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| Exercises | |
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| Multiple Imputation: Methods and Applications for Survey Analysts | |
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| Introduction | |
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| Important Missing Data Concepts | |
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| An Introduction to Imputation and the Multiple Imputation Method | |
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| Models for Multiply Imputing Missing Data | |
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| Creating the Imputations | |
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| Estimation and Inference for Multiply Imputed Data | |
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| Applications to Survey Data | |
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| Exercises | |
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| Advanced Topics in the Analysis of Survey Data | |
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| Introduction | |
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| Bayesian Analysis of Complex Sample Survey Data | |
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| Generalized Linear Mixed Models (GLMMs) in Survey Data Analysis | |
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| Fitting Structural Equation Models to Complex Sample Survey Data | |
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| Small Area Estimation and Complex Sample Survey Data | |
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| Nonparametric Methods for Complex Sample Survey Data | |
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| References | |
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| Appendix: Software Overview | |