Publications by Daniel
Bayesian Regression Modelling in R: Choosing informative priors in rstanarm #rstats
Yesterday, at the last meeting of the Hamburg R User Group in this year, I had the pleasure to give a talk about Bayesian modelling and choosing (informative) priors in the rstanarm-package. You can download the slides of my talk here. Thanks to the Stan team and Tristan for proof reading my slides prior ( Tagged: Bayes, R, regression, rstats, St...
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Data transformation in #tidyverse style: package sjmisc updated #rstats
I’m pleased to announce an update for the sjmisc-package, which was just released on CRAN. Here I want to point out two important changes in the package. New default option for recoding and transformation functions First, a small change in the code with major impact on the workflow, as it affects argument defaults and is likely to break your ex...
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Anova-Freak and Bayesian Hipster #rstats
I’m pleased to announce an update of my sjstats-package. New features are specifically implemented for the Anova and Bayesian statistic and summary functions. Here’s a short overview of what’s new… Anova statistics Beside the already implemented functions to calculate eta-squared, partial eta-squared and omega-squared, it is now also pos...
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R functions for Bayesian Model Statistics and Summaries #rstats #stan #brms
A new update of my sjstats-package just arrived at CRAN. This blog post demontrates those functions of the sjstats-package that deal especially with Bayesian models. The update contains some new and some revised functions to compute summary statistics of Bayesian models, which are now described in more detail. hdi() rope() mcse() n_eff() tidy_st...
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Marginal Effects for Regression Models in R #rstats #dataviz
Regression coefficients are typically presented as tables that are easy to understand. Sometimes, estimates are difficult to interpret. This is especially true for interaction or transformed terms (quadratic or cubic terms, polynomials, splines), in particular for more complex models. In such cases, coefficients are no longer interpretable in a d...
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Marginal Effects for (mixed effects) regression models #rstats
ggeffects (CRAN, website) is a package that computes marginal effects at the mean (MEMs) or representative values (MERs) for many different models, including mixed effects or Bayesian models. One of the advantages of the package is its easy-to-use interface: No matter if you fit a simple or complex model, with interactions or splines, the functio...
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ggeffects 0.8.0 now on CRAN: marginal effects for regression models #rstats
I’m happy to announce that version 0.8.0 of my ggeffects-package is on CRAN now. The update has fixed some bugs from the previous version and comes along with many new features or improvements. One major part that was addressed in the latest version are fixed and improvements for mixed models, especially zero-inflated mixed models (fitted with ...
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R and labelled data: Using quasiquotation to add variable and value labels #rstats
Labelling data is typically a task for end-users and is applied in own scripts or functions rather than in packages. However, sometimes it can be useful for both end-users and package developers to have a flexible way to add variable and value labels to their data. In such cases, quasiquotation is helpful. This vignette demonstrate how to use q...
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Quickly create Codeplans of your (labelled) Data #rstats
The view_df() function from the sjPlot-package creates nice „codeplans“ from your data sets, and also supports labelled data and tagged NA-values. This gives you a comprehensive, yet clear overview of your data set. To demonstrate this function, we use a (labelled) data set from the European Social Survey. view_df() produces a HTML-file, ...
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Likert-plots and grouped Likert-plots #rstats
I’m pleased to anounce an update of my sjPlot-package, a package for Data Visualization for Statistics in Social Science. Thanks to the help of Alexander, it is now possible to create grouped Likert-plots. This is what I want to show in this post… First, we load the required packages and sample data. We want to plot several items from an ind...
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