University of Massachusetts Amherst

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CRF Methodology Workshop Series June 2013

The Center for Research on Families’ Summer Methodology Workshop Series is now in its eighth year and is hosting four workshops in June. The workshops are held by leading researchers in the field and will provide hands-on experience regarding a variety of topics.





This summer’s workshops include:

Analyzing Developmental Trajectories  |  June 3-5, 2013
Instructor: Dr. Daniel Nagin, Carnegie-Mellow University
A developmental trajectory describes the course of a behavior over age or time. This two and a half day workshop aims to provide participants with the training to apply a group-based method for analyzing developmental trajectories. 

Hierarchical Linear Models: Introduction | June 10-14, 2013
Instructors: Dr. Aline Sayer, University of Massachusetts Amherst and Dr. Mark Manning, Wayne State University
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. Participants will be exposed to a wide variety of examples, with emphasis on the interpretation and reporting of results.

Workflow of Data Analysis using Stata| June 17-21, 2013
Instructor: Dr. 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.

Analyzing Intensive Longitudinal Data | June 25-28, 2013
Instructors: Dr. Jean-Philippe Laurenceau, University of Delaware and Dr. Niall Bolger, Columbia University
These intensive longitudinal methods allow researchers to examine processes in daily life in a way that is not possible using traditional methods. However, longitudinal data present several data analytic challenges stemming from the various possible sources of interdependence in these data. The course will include lectures, software demonstrations, and computer lab work.

Registration is currently open, so we encourage you to get more information about the sessions and register here