The mission of The Methodology Center is to advance public health by improving experimental design and data analysis in the social, behavioral, and health sciences.
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Discovering Hidden Subgroups
Latent class analysis (LCA) allows researchers to detect the existence of subgroups within populations. Latent transition analysis (LTA) extends LCA to changes in group membership over time.
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Analyzing Rich, Complex Data Sets
Our intensive longitudinal data project provides tools for analyzing data with many observations, like data collected in smartphone studies. Our high-dimensional data project provides tools for variable selection and analysis of datasets with large numbers of variables, like genetics data.
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Designing and Building Health Interventions
The sequential, multiple assignment, randomized trial (SMART) project provides tools for building adaptive interventions so that treatments adapt to meet patients’ needs. The multiphase optimization strategy (MOST) is a framework for engineering interventions for purposes such as maximizing intervention potency within a specified cost limit or streamlining existing interventions for scale-up.
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Inferring Cause Without Randomization
Social, behavioral, and health researchers often face situations where randomization is not possible, practical, or ethical. Our causal inference project develops methods for inferring causality in non-randomized experiments or studies.
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May 9, 2012
We are pleased to announce the publication of a new book on missing data for non-statisticians. Missing Data: Analysis and Design was written by 