Overview of MATI

The workshop will include 5 days of training and one day of group presentations. Each day will include 3 sessions and will conclude with time to work on the group project. The integrative project will provide participants with an opportunity to practice developing an IES Goal 1 meta-analysis research proposal.

Advanced Statistical Methods

Topics will include:

• Advanced effect sizes (e.g., pre-post, regression coefficients, clustered)

• Power analysis for main effects and moderators

• Methods for handling dependent effect sizes (robust variance estimation)

• Meta-regression 

• Missing data (both outcomes and moderators)

• Publication bias

• Meta-SEM

• Single-case designs

• Interpretation of results (particularly with heterogeneity)

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Implementation of Methods in R

Students will learn to:

• Use metafor to calculate effect sizes and conduct simple meta-analyses

• Use robumeta and clubSandwich to implement robust variance estimation

• Use metaSEM to estimate meta-SEM models

• Use R more generally to create funnel plots, impute missing data, and conduct power analysis

Project Management Skills

Topics will include:

• Choosing a database management system (e.g., FileMaker vs Excel)

• Setting up a database

• Training coders and assessing reliability

• Budgeting

• Scoping and coding

• Timelines

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