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.


Information Matrices for 'lmeStruct' and 'glsStruct' Objects


Helper package to assist in running simulation studies

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.

CRAN downloads of my packages

At AERA this past weekend, one of the recurring themes was how software availability (and its usability and default features) influences how people conduct meta-analyses. That got me thinking about the R packages that I’ve developed, how to understand the extent to which people are using them, how they’re being used, and so on.

clubSandwich at the Austin R User Group Meetup

Last night I attended a joint meetup between the Austin R User Group and R Ladies Austin, which was great fun. The evening featured several lightning talks on a range of topics, from breaking into data science to network visualization to starting your own blog.

Pooling clubSandwich results across multiple imputations

A colleague recently asked me about how to apply cluster-robust hypothesis tests and confidence intervals, as calculated with the clubSandwich package, when dealing with multiply imputed datasets. Standard methods (i.

Imputing covariance matrices for meta-analysis of correlated effects

In many systematic reviews, it is common for eligible studies to contribute effect size estimates from not just one, but multiple relevant outcome measures, for a common sample of participants.

Bug in nlme::lme with fixed sigma and REML estimation

About one year ago, the nlme package introduced a feature that allowed the user to specify a fixed value for the residual variance in linear mixed effect models fitted with lme().

Simulation studies in R (Fall, 2016 version)

In today’s Quant Methods colloquium, I gave an introduction to the logic and purposes of Monte Carlo simulation studies, with examples written in R. Here are the slides from my presentation.