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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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