Rstats

New article: Alternating renewal process models for behavioral observation

My article with Chris Runyon, titled “Alternating renewal process models for behavioral observation: Simulation methods, software , and validity illustrations” has been published in Behavioral Disorders. The abstract is below.

ARPobservation now on CRAN

Version 1.0 of the ARPobservation package is now available on the Comprehensive R Archive Network. This makes it even easier to install. Here’s the package description: ARPobservation: Tools for simulating different methods of observing behavior based on alternating renewal processes

Meta-sandwich with extra mustard

In an earlier post about sandwich standard errors for multi-variate meta-analysis, I mentioned that Beth Tipton has recently proposed small-sample corrections for the covariance estimators and t-tests, based on the bias-reduced linearization approach of McCaffrey, Bell, and Botts (2001).

Another meta-sandwich

In a previous post, I provided some code to do robust variance estimation with metafor and sandwich. Here’s another example, replicating some more of the calculations from Tanner-Smith & Tipton (2013).

A meta-sandwich

A common problem arising in many areas of meta-analysis is how to synthesize a set of effect sizes when the set includes multiple effect size estimates from the same study.

Update: parallel R on the TACC

I have learned from Mr. Yaakoub El Khamra that he and the good folks at TACC have made some modifications to TACC’s custom MPI implementation and R build in order to correct bugs in Rmpi and snow that were causing crashes.

Running R in parallel on the TACC

UPDATE (4/8/2014): I have learned from Mr. Yaakoub El Khamra that he and the good folks at TACC have made some modifications to TACC’s custom MPI implementation and R build in order to correct bugs in Rmpi and snow that were causing crashes.

Designing simulation studies using R

Here are the slides from my presentation at this afternoon’s Quant. Methods brown bag. I gave a very quick introduction to using R for conducting simulation studies. I hope it was enough to get people intrigued about the possibilities of using R in their own work.

ARPobservation: Basic use

The ARPobservation package provides a set of tools for simulating data generated by different procedures for direct observation of behavior. This is accomplished in two steps. The first step is to simulate a “behavior stream” itself, which is assumed to follow some type of alternating renewal process.

Getting started with ARPobservation

UPDATED 5/29/2014 after posting the package to CRAN Here are step-by-step instructions on how to download and install ARPobservation. For the time being, ARPobservation is available as a pre-compiled binary for Windows.