Quick #sjPlot status update… #rstats #rstanarm #ggplot2

I’m working on the next update of my sjPlot-package, which will get a generic plot_model() method, which plots any kind of regression model, with different plot types being supported (forest plots for estimates, marginal effects and predictions, including displaying interaction terms, …). The package also supports rstan resp. rstanarm models. Since these are typically presented […]

Marginal effects for negative binomial mixed effects models (glmer.nb and glmmTMB) #rstats

Here’s a small preview of forthcoming features in the ggeffects-package, which are already available in the GitHub-version: For marginal effects from models fitted with glmmTMB() or glmer() resp. glmer.nb(), confidence intervals are now also computed. If you want to test these features, simply install the package from GitHub: library(devtools) devtools::install_github(„strengejacke/ggeffects“) Here are three examples: library(glmmTMB) […]

Going Bayes #rstats

Some time ago I started working with Bayesian methods, using the great rstanarm-package. Beside the fantastic package-vignettes, and books like Statistical Rethinking or Doing Bayesion Data Analysis, I also found the ressources from Tristan Mahr helpful to both better understand Bayesian analysis and rstanarm. This motivated me to implement tools for Bayesian analysis into my […]

My set of packages for (daily) data analysis #rstats

I started writing my first package as collection of various functions that I needed for (almost) daily work. Meanwhile, packages were growing and bit by bit I sourced out functions to put them into new packages. Although this means more work for CRAN members when they have more packages to manage on their network, from […]

Direct integration of sjPlot-tables in knitr-rmarkdown-documents #rstats

A new update of my sjPlot-package was just released on CRAN. Thanks to @c_schwemmer, it’s now possible to easily integrate the HTML-ouput of all table-functions into knitr-rmarkdown-documents. Simpel Tables In the past, to integrate table-output in knitr, you needed to set the argument no.output = TRUE and use the return-value $knitr: If you also wanted […]

Exploring the European Social Survey (ESS) – pipe-friendly workflow with sjmisc, part 2 #rstats #tidyverse

This is another post of my series about how my packages integrate into a pipe-friendly workflow. The post focusses on my sjmisc-package, which was just updated on CRAN, and highlights some of the new features. Examples are based on data from the European Social Survey, which are freely available. Please note: The statistical analyses at […]

Tagged NA values and labelled data #rstats

sjmisc-package: Working with labelled data A major update of my sjmisc-package was just released an CRAN. A major change (see changelog for all changes )is the support of the latest release from the haven-package, a package to import and export SPSS, SAS or Stata files. The sjmisc-package mainly addresses three domains: reading and writing data […]