Posts

Finding the distribution of significant effect sizes

In basic meta-analysis, where each study contributes just a single effect size estimate, there has been a lot of work devoted to developing models for selective reporting. Most of these models formulate the selection process as a function of the statistical significance of the effect size estimate; some also allow for the possibility that the precision of the study’s effect influences the probability of selection (i.

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.

An update on code folding with blogdown + Academic theme

UPDATED November 21, 2020. Thanks to Allen O’Brien for pointing out a bug in the codefolding code, which led to the last code chunk defaulting to hidden rather than open.

Simulating correlated standardized mean differences for meta-analysis

As I’ve discussed in previous posts, meta-analyses in psychology, education, and other areas often include studies that contribute multiple, statistically dependent effect size estimates. I’m interested in methods for meta-analyzing and meta-regressing effect sizes from data structures like this, and studying this sort of thing often entails conducting Monte Carlo simulations.

Sometimes, aggregating effect sizes is fine

In meta-analyses of psychology, education, and other social science research, it is very common that some of the included studies report more than one relevant effect size. For example, in a meta-analysis of intervention effects on reading outcomes, some studies may have used multiple measures of reading outcomes (each of which meets inclusion criteria), or may have measured outcomes at multiple follow-up times; some studies might have also investigated more than one version of an intervention, and it might be of interest to include effect sizes comparing each version to the no-intervention control condition; and it’s even possible that some studies may have all of these features, potentially contributing lots of effect size estimates.

Code folding with blogdown + Academic theme

2020-05-03 This post describes an implementation of code folding for an older version of the Academic Theme. It does not work with Academic 4.+. See my updated instructions to get it working with newer versions of Academic.