Bridging Advanced Quantitative Methods and Applied Research in the Behavioral, Social and Health Sciences

BRIDGING ADVANCED QUANTITATIVE METHODS WITH APPLIED RESEARCH IN THE BEHAVORIAL, SOCIAL & HEALTH SCIENCES

Training

We currently offer workshops on Multilevel Modeling, Structural Equation Modeling, Structural Equation Models for Longitudinal Data, Mixture Models and Cluster Analysis, and Network Analysis. We also provide individually tailored instruction to groups with specific data analytic needs.

Consulting

We provide consulting services on each phase of the research process, from study design to the application and interpretation of quantitative methods. We offer several modes of consulting to suit a variety of needs.

Informing

We seek to provide you with the information you need to be a knowledgeable user of quantitative methods, including updates on ongoing developments in the field, discussion of common data analytic concerns, and tutorials on commonly used techniques.

LATEST NEWS

What is the difference between a growth model estimated as a multilevel model versus as a structural equation model?

February 18, 2019

This very common question reflects a great deal of unnecessary confusion about how to select a specific analytic approach for modeling longitudinal data. The general term “growth modeling” refers to a variety of statistical methods that allow for the estimation of inter-individual (or between-person) differences in intra-individual (or within-person) change. Often, the function describing within-person change is referred to as a “growth curve” or “trajectory” and can produce different patterns from person to person: trajectories might be flat (not changing over time) or they might be systematically increasing or decreasing in some linear or non-linear form over time. These trajectories might be the primary focus of analysis or they might represent just part of a more complex longitudinal model. Regardless of purpose, there are two general approaches most often used to fit growth models to sample data.

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