Blog Archives

Beautiful table-outputs: Summarizing mixed effects models #rstats

June 4, 2015
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Beautiful table-outputs: Summarizing mixed effects models #rstats

The current version 1.8.1 of my sjPlot package has two new functions to easily summarize mixed effects models as HTML-table: sjt.lmer and sjt.glmer. Both are very similar, so I focus on showing how to use sjt.lmer here. Linear mixed models summaries as HTML table The sjt.lmer function prints summaries of linear mixed models (fitted with

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sjmisc – package for working with (labelled) data #rstats

May 22, 2015
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sjmisc – package for working with (labelled) data #rstats

The sjmisc-package My last posting was about reading and writing data between R and other statistical packages like SPSS, Stata or SAS. After that, I decided to bundle all functions that are not directly related to plotting or printing tables, into a new package called sjmisc. Basically, this package covers three domains of functionality: reading

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Reading from and writing to SPSS, SAS and STATA with R #rstats #sjPlot

March 11, 2015
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Reading from and writing to SPSS, SAS and STATA with R #rstats #sjPlot

On CRAN now My sjPlot-package was updated on CRAN (binaries will be available soon, I guess). This update contains, besides many small improvements and fixes, two major features: First, new features to print table summaries of linear models and generalized linear models (for sjt.glm, the same new features were added as to sjt.lm – however,

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CRAN download statistics of any packages #rstats

March 7, 2015
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CRAN download statistics of any packages #rstats

Hadley Wickham announced at Twitter that RStudio now provides CRAN package download logs. I was wondering about the download numbers of my package and wrote some code to extract that information from the logs… The first code snippet is taken from the log website itself: Then I downloaded all files into a folder: Unzipping did

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Beautiful tables for linear model summaries #rstats

March 6, 2015
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Beautiful tables for linear model summaries #rstats

Beautiful HTML tables of linear models In this blog post I’d like to show some (old and) new features of the sjt.lm function from my sjPlot-package. These functions are currently only implemented in the development snapshot on GitHub. A package update is planned to be submitted soon to CRAN. There are two new major features

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sjPlot package and related online manuals updated #rstats # ggplot

February 5, 2015
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sjPlot package and related online manuals updated #rstats # ggplot

My sjPlot package for data visualization has just been updated on CRAN. I’ve added some features to existing function, which I want to introduce here. Plotting linear models So far, plotting model assumptions of linear models or plotting slopes for each estimate of linear models were spread over several functions. Now, these plot types have

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Visualizing (generalized) linear mixed effects models, part 2 #rstats #lme4

November 18, 2014
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Visualizing (generalized) linear mixed effects models, part 2 #rstats #lme4

In the first part on visualizing (generalized) linear mixed effects models, I showed examples of the new functions in the sjPlot package to visualize fixed and random effects (estimates and odds ratios) of (g)lmer results. Meanwhile, I added further features to the functions, which I like to introduce here. This posting is based on the

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Visualizing (generalized) linear mixed effects models with ggplot #rstats #lme4

October 26, 2014
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Visualizing (generalized) linear mixed effects models with ggplot #rstats #lme4

In the past week, colleagues of mine and me started using the lme4-package to compute multi level models. This inspired me doing two new functions for visualizing random effects (as retrieved by ranef()) and fixed effects (as retrieved by fixed()) of (generalized) linear mixed effect models. The upcoming version of my sjPlot package will contain

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sjPlot 1.6 – major revisions, anyone for beta testing? #rstats

October 23, 2014
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sjPlot 1.6 – major revisions, anyone for beta testing? #rstats

In the last couple of weeks I have rewritten some core parts of my sjPlot-package and also revised the package- and online documentation. Most notably are the changes that affect theming and appearance of plots and figures. There’s a new function called sjp.setTheme which now sets theme-options for all sjp-functions, which means you only need

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Visualize pre-post comparison of intervention #rstats

August 19, 2014
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Visualize pre-post comparison of intervention #rstats

My sjPlot-package was just updated on CRAN, introducing a new function called sjp.emm.int to plot estimated marginal means (least-squares means) of linear models with interaction terms. Or: plotting adjusted means of an ANCOVA. The idea to this function came up when we wanted to analyze the effect of an intervention (an educational programme on knowledge

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