The hierarchical linear model (HLM) provides a conceptual framework and a flexible set of analytic tools to study a variety of social, political, and developmental processes. One set of applications focuses on data in which persons are clustered within social contexts, such as couples, families, schools, neighborhoods, or organizations.
Dr. Aline Sayer, University of Massachusetts Amherst
Dr. Mark Manning, Wayne State University
Dr. Daniel Nagin, Carnegie-Mellon University
A developmental trajectory describes the course of a behavior over age or time. This two and a half days workshop aims to provide participants with the training to apply a group-based method for analyzing developmental trajectories.
Dr. Jean-Philippe Laurenceau, University of Delaware
Dr. Niall Bolger, Columbia University
In recent decades, researchers have become increasingly interested in understanding people’s thoughts, emotions, and behaviors in their natural contexts. The commonality in methods for doing so—experience sampling, daily diary, and ecological momentary assessment methods—is that they all involve intensive longitudinal assessments.
Scott Long, Distinguished Professor of Sociology and Statistics, Indiana University
This intensive workshop deals with the workflow of data analysis. Workflow encompasses the entire process of scientific research: planning, documenting, and organizing your work; creating, labeling, naming, and verifying variables; performing and presenting statistical analyses; preserving your work; and, critically, producing replicable results. Most classes in statistics focus on estimating and interpreting models. In "real world" research, these activities often involve less than 10% of the total work. This workshop is about the other 90% of the work.