James E. Pustejovsky

I am a statistician and associate professor in the School of Education at the University of Wisconsin-Madison, where I teach in the Educational Psychology Department and the graduate program in Quantitative Methods. My research involves developing statistical methods for problems in education, psychology, and other areas of social science research, with a focus on methods related to research synthesis and meta-analysis.


  • Meta-analysis
  • Causal inference
  • Robust statistical methods
  • Education statistics
  • Single case experimental designs


  • PhD in Statistics, 2013

    Northwestern University

  • BA in Economics, 2003

    Boston College

Recent Posts

The Woodbury identity

As in many parts of life, statistics is full of little bits of knowledge that are useful if you happen to know them, but which hardly anybody ever bothers to mention.

An ANCOVA puzzler

Doing effect size calculations for meta-analysis is a good way to lose your faith in humanity—or at least your faith in researchers’ abilities to do anything like sensible statistical inference.

From Longhorn to Badger

It’s taken me a while to finally get around to updating my website with some personal news. I’ve moved from UT Austin to the UW Madison School of Education, where I am now an associate professor in the Educational Psychology Department’s Quantitative Methods program.

What do meta-analysts mean by 'multivariate' meta-analysis?

If you’ve ever had class with me or attended one of my presentations, you’ve probably heard me grouse about how statisticians are mostly awful about naming things.1 A lot of the terminology in our field is pretty bad and ineloquent.

Weighting in multivariate meta-analysis

One common question about multivariate/multi-level meta-analysis is how such models assign weight to individual effect size estimates. When a version of the question came up recently on the R-sig-meta-analysis listserv, Dr.

Working papers

Meta-Analysis with robust variance estimation: Expanding the range of working models

In prevention science and related fields, large meta-analyses are common, and these analyses often involve dependent effect size estimates. Robust variance estimation (RVE) methods provide a way to …

Recent Publications

Systematic review and meta-analysis of stay-play-talk interventions for improving social behaviors of young children

Stay-play-talk (SPT) is a peer-mediated intervention which involves training peer implementers to stay in proximity to, play with, and talk to a focal child who has disabilities or lower social …

Evaluating meta-analytic methods to detect selective reporting in the presence of dependent effect sizes

Meta-analysis is a set of statistical tools used to synthesize results from multiple studies evaluating a common research question. Two methodological challenges when conducting meta-analysis include …

The impact of response-guided designs on count outcomes in single-case experimental design baselines

In single-case experimental design (SCED) research, researchers often choose when to start treatment based on whether the baseline data collected so far are stable, using what is called a …

Psychosocial interventions for cancer survivors: A meta-analysis of effects on positive affect

Purpose Positive affect has demonstrated unique benefits in the context of health-related stress and is emerging as an important target for psychosocial interventions. The primary objective of this …

An examination of measurement procedures and characteristics of baseline outcome data in single-case research

There has been growing interest in using statistical methods to analyze data and estimate effect size indices from studies that use single-case designs (SCDs), as a complement to traditional visual …

Recent Presentations

A generalized excess significance test for selective outcome reporting with dependent effect sizes

Log response ratio effect sizes: Rationale and methods for single case designs with behavioral outcomes

Evaluating meta-analytic methods to detect outcome reporting bias in the presence of dependent effect sizes

An examination of measurement procedures and baseline behavioral outcomes in single-case research

The impact of response-guided designs on count outcomes in single-case design baselines



Information Matrices for ‘lmeStruct’ and ‘glsStruct’ Objects


Helper package to assist in running simulation studies


Simulate systematic direct observation data


Cluster-robust variance estimation


Between-case SMD for single-case designs


Single-case design effect size calculator


Current Advisees


Man Chen

Graduate student


Megha Joshi

Doctoral candidate


Young Ri Lee

Graduate student



Christopher Runyon

Measurement Scientist



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