Install R without support for long doubles (noLD) on Ubuntu

R packages on CRAN needs to pass a series of technical checks. These checks can also be invoked by any user when running R CMD check on the package tar.gz (to emulate CRAN as much as possible one should also set the –as-cran option when doing so). These checks need to be passed before a […]

afex_plot(): Publication-Ready Plots for Factorial Designs

I am happy to announce that a new version of afex (version 0.22-1) has appeared on CRAN. This version comes with two major changes, for more see the NEWS file. To get the new version including all packages used in the examples run: install.packages(“afex”, dependencies = TRUE) First, afex does not load or attach package […]

Diffusion/Wiener Model Analysis with brms – Part III: Hypothesis Tests of Parameter Estimates

This is the third part of my blog series on fitting the 4-parameter Wiener model with brms. The first part discussed how to set up the data and model. The second part was concerned with (mostly graphical) model diagnostics and the assessment of the adequacy (i.e., the fit) of the model. This third part will […]

Diffusion/Wiener Model Analysis with brms – Part II: Model Diagnostics and Model Fit

This is the considerably belated second part of my blog series on fitting diffusion models (or better, the 4-parameter Wiener model) with brms. The first part discusses how to set up the data and model. This second part is concerned with perhaps the most important steps in each model based data analysis, model diagnostics and […]

Diffusion/Wiener Model Analysis with brms – Part I: Introduction and Estimation

Stan is probably the most interesting development in computational statistics in the last few years, at least for me. The version of Hamiltonian Monte-Carlo (HMC) implemented in Stan (NUTS, ) is extremely efficient and the range of probability distributions implemented in the Stan language allows to fit an extremely wide range of models. Stan has […]

ANOVA in R: afex may be the solution you are looking for

Prelude: When you start with R and try to estimate a standard ANOVA , which is relatively simple in commercial software like SPSS, R kind of sucks. Especially for unbalanced designs or designs with repeated-measures replicating the results from such software in base R may require considerable effort. For a newcomer (and even an old […]

Mixed models for ANOVA designs with one observation per unit of observation and cell of the design

Together with David Kellen I am currently working on an introductory chapter to mixed models for a book edited by Dan Spieler and Eric Schumacher (the current version can be found here). The goal is to provide a theoretical and practical introduction that is targeted mainly at experimental psychologists, neuroscientists, and others working with experimental […]

rtdists 0.7-2: response time distributions now with Rcpp and faster

It took us quite a while but we have finally released a new version of rtdists to CRAN which provides a few significant improvements. As a reminder, rtdists [p]rovides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation): (a) Ratcliff diffusion model based on C code by Andreas and Jochen Voss and (b) […]

New Version of rtdists on CRAN (v. 0.4-9): Accumulator Models for Response Time Distributions

I have just submitted a new version of rtdists to CRAN (v. 0.4-9). As I haven’t mentioned rtdists on here yet, let me simply copy it’s description as a short introduction, a longer introduction follows below: Provides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation): (a) Ratcliff diffusion model based on C […]

Hierarchical MPT in Stan I: Dealing with Convergent Transitions via Control Arguments

I have recently restarted working with Stan and unfortunately ran into the problem that my (hierarchical) Bayesian models often produced divergent transitions. And when this happens, the warning basically only suggests to increase adapt_delta: Warning messages: 1: There were X divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. 2: Examine the pairs() plot […]