Methodology Program
2007 - Workshops
ANALYZING DEVELOPMENTAL TRAJECTORIES
June 19-21, 2007University of Massachusetts Amherst
Instructor: Daniel Nagin, professor of Public Policy and Statistics at Carnegie-Mellon University.
A developmental trajectory describes the course of a behavior over age or time. This workshop aims to provide participants with the training to apply a group-based method for analyzing developmental trajectories. This methodology has four significant capabilities: (1) the capability to identify rather than assume distinctive groups of trajectories, (2) the capability to estimate the proportion of the population following each such trajectory group, (3) the capability to relate group membership probability to individual characteristics and circumstances, and (4) the capability to use the group membership probabilities for various other purposes such as creating profiles of group members. In addition, workshop participants will be trained in the application of three important extensions of the method: (1) the capability to add time-varying covariates to trajectory models, (2) the capability to estimate joint trajectory models of distinct but related behaviors, and (3) the capability to link trajectories with distal outcomes. This workshop is offered in collaboration with the Inter-University Consortium for Political and Social Research (ICPSR) at the University of Michigan.
HIERARCHICAL LINEAR MODELS I
June 25-29, 2007University of Massachusetts Amherst
Instructors: Aline Sayer, associate professor of psychology and CRF's Methodology Program Director at UMass Amherst, and Natalya Verbitsky, Research Scientist in Statistics at the University of Chicago.
Hierarchical linear models (HLMs) provide a conceptual framework and a flexible set of analytical tools to study a variety of social, political, and developmental processes. ne major HLM application focuses on the modeling of longitudinal data or the analysis of individual change over time. Another set of applications focuses on data in which persons are clustered within social context such as schools, neighborhoods, or organizations. Participants will be exposed to a wide variety of examples, with emphasis on the interpretation and reporting of results. This workshop is offered in collaboration with the Inter-University Consortium for Political and Social Research (ICPSR) at the University of Michigan.
MODELING LONGITUDINAL AND DYADIC DATA WITH HLM
July 23-25, 2007University of Massachusetts Amherst
Instructor: Aline Sayer, associate professor of psychology and CRF's Methodology Program Director at UMass Amherst.
Information: Monday-Wednesday; 9:00-4:30 p.m.,
Room 1001, Campus Center, University of Massachusetts Amherst
Workshop fee : $500 General/$350 Students/$350 CRF Affiliates (optional 2 CEU credits available: $24).
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 major application focuses on the modeling of longitudinal data where time series data are clustered within persons. A second application concerns the analysis of dyads, where individual responses are clustered within couples, sibships, caregiving dyads or other matched pairs. This workshop will consider the formulation of statistical models for these two applications using the HLM6 software package.
The workshop will provide an introduction to the basic two-level model for polynomial growth functions, splines (piecewise growth models), checking model assumptions, multiparameter hypothesis testing, the incorporation of time-varying covariates, and multivariate models for growth, with consideration of a variety of alternative covariance structures. Learning the computing necessary to fit the models is an integral part of the course.
After a brief review of older methods for analyzing dyads, the workshop will focus specifically on the HLM modeling approach for analyzing dyadic data. These include dyadic consensus and discrepancy, multivariate outcomes, and the actor-partner interdependence model. Special models for exchangeable dyads (such as identical twins or same-sex friendship pairs) and the extension to longitudinal models will also be presented.
The course will meet 8 hours per day, with equal time devoted to lecture-demonstration and a computer lab using the HLM program. Participants should have strong backgrounds in multiple regression analysis.
