Although selecting a probability sample has been the standard for decades when making
inferences from a sample to a finite population, incentives are increasing to use …

Highly recommended by the Journal of Official Statistics, The American Statistician, and
other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date …

In this article, we review current state-of-the art software enabling statisticians to apply
design-based, model-based, and so-called “hybrid” approaches to the analysis of complex …

Introduction Even prior to 2018, electronic nicotine delivery systems (ENDS) began to
dramatically change the landscape of tobacco products and product use patterns in the …

Multiple imputation is now well established as a practical and flexible method for analyzing
partially observed data, particularly under the missing at random assumption. However …

The idea to generate synthetic data as a tool for broadening access to sensitive microdata
has been proposed for the first time three decades ago. While first applications of the idea …

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies
provides a comprehensive introduction to the multiple imputation approach to missing data …

This study contributes new evidence on the factors associated with undergraduate study
abroad participation and post-college volunteering. Drawing on Education Longitudinal …

Complex sampling designs involving features such as stratification, cluster sampling, and
unequal selection probabilities are often used in large-scale longitudinal surveys to improve …

Multiple Imputation in Practice: With Examples Using IVEware provides practical guidance
on multiple imputation analysis, from simple to complex problems using real and simulated …