Here are descriptions from a few of the Methodology workshops held in the past:

Analyzing Developmental Trajectories

A developmental trajectory describes the course of a behavior over age or time. This three-day 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
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
3. The capability to link trajectories with distal outcomes.

Hierarchical Linear Models I: An Introduction

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.

Modeling Diary and Dyadic Data

This workshop is for social psychologists, family and medical sociologists, gerontologists, social workers, communication researchers, and researchers of marketing and organizational behavior. Diary methods allow researchers to examine dyadic processes in daily life in a way that is not possible using traditional methods. Using diaries, researchers typically obtain many repeated observations on dyad members over days and weeks. Dyadic diary data, however, present several data analytic challenges stemming from the various sources of interdependence in these data. Not only is there non-independence between members of the dyad, there is also non-independence of observations within each dyad member. The multilevel or hierarchical linear model (HLM) provides a flexible set of analytic tools that can take account of these complexities. This workshop will begin by considering models for diary data on individuals. It will then cover models for the analysis of dyads, where individual responses are clustered within couples, sibships, caregiving dyads, or other matched pairs. Finally, it will cover models for dyadic diary data. The course will devote equal time to lectures/demonstrations by the presenters and computer lab work by the participants. The main software used will be HLM6 with some advanced applications using SAS PROC MIXED and Mplus. Participants should have strong backgrounds in multiple regression analysis.

Modeling Longitudinal and Dyadic Data with HLM

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.

What to Do About Missing Data: Tools for Practitioners

The workshop focuses on modern approaches to missing data and presented models for missing continuous, categorical, mixture of continuous and categorical and panel data. The workshop was both theoretical and included hands-on lessons on the software that can be used for implementing the modern methods.