Publications by Daniel
Descriptive summary: Proportions of values in a vector #rstats
When describing a sample, researchers in my field often show proportions of specific characteristics as description. For instance, proportion of female persons, proportion of persons with higher or lower income etc. Since it happens often that I like to know these characteristics when exploring data, I decided to write a function, prop(), which i...
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Negative Binomial Regression for Complex Samples (Surveys) #rstats
The survey-package from Thomas Lumley is a great toolkit when analyzing complex samples. It provides svyglm(), to fit generalised linear models to data from a complex survey design. svyglm() covers all families that are also provided by R’s glm() – however, the survey-package has no function to fit negative binomial models, which might be use...
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ggeffects: Create Tidy Data Frames of Marginal Effects for ‚ggplot‘ from Model Outputs #rstats
Aim of the ggeffects-package The aim of the ggeffects-package is similar to the broom-package: transforming “untidy” input into a tidy data frame, especially for further use with ggplot. However, ggeffects does not return model-summaries; rather, this package computes marginal effects at the mean or average marginal effects from statistical...
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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 a user-perspective it is mu...
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Effect Size Statistics for Anova Tables #rstats
My sjstats-package has been updated on CRAN. The past updates introduced new functions for various purposes, e.g. predictive accuracy of regression models or improved support for the marvelous glmmTMB-package. The current update, however, added some ANOVA tools to the package. In this post, I want to give a short overview of these new functions,...
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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...
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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)...
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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....
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More support for Bayesian analysis in the sj!-packages #rstats #rstan #brms
Another quick preview of my R-packages, especially sjPlot, which now also support brmsfit-objects from the great brms-package. To demonstrate the new features, I load all my „core“-packages at once, using the strengejacke-package, which is only available from GitHub. This package simply loads four packages (sjlabelled, sjmisc, sjstats and sjP...
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„One function to rule them all“ – visualization of regression models in #rstats w/ #sjPlot
I’m pleased to announce the latest update from my sjPlot-package on CRAN. Beside some bug fixes and minor new features, the major update is a new function, plot_model(), which is both an enhancement and replacement of sjp.lm(), sjp.glm(), sjp.lmer(), sjp.glmer() and sjp.int(). The latter functions will become deprecated in the next updates and ...
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