This chapter provides a brief introduction to R Markdown, as well as the papaja package to produce output in the APA style. ![]() For instance, this book was completely written in R Markdown, with help from the additional bookfown package ( ). R Markdown is extremely flexible and useful. Anyone with the R Markdown file would be able to reproduce everything in a scientific paper. ![]() Including all analysis in the same document allows for completely reproducible research. A big benefit of this is that can keep your analysis and write-up in one place, so you don’t have to copy-paste results from one place to another (which often results in errors and issues). Markdown documents can be “parsed” to produce documents in a variety of formats, including HTML, PDF, Open Document Type, Microsoft Word, you name it… R Markdown integrates Markdown with R, allowing you to use R to include figures, tables, and R output (as well as the corresponding code, if you wish) directly in the document. Markdown itself is a lightweight markup language, with a plain-text formatting syntax. One of the many things that makes R extremely useful as a data analysis platform is its ability to generate high-quality reproducible reports and documents via R Markdown. 13.1.5 Bayesian repeated-measures ANOVAĬhapter 14 Reproducible reports with RMarkdown.13 Bayesian hypothesis testing with Bayes Factors.11 Structural Equation modelling with lavaan.9.2 Obtaining p-values with afex::mixed.9.1.4 Likelihood ratio test with the anova function.9.1.2 Visually assessing model assumptions.9.1 Formulating and estimating linear mixed-effects models with lme4.8.4 Repeated-measures ANOVA with the afex package.8.3 Repeated-measures ANOVA with the car package.8.2.2 Performing a repeated-measures ANOVA with separate models.8.2.1 Computing within-subjects composite scores.8.2 Repeated-measures ANOVA with separate GLMs.7.5 Testing general contrasts with emmeans.7.4 Planned comparisons and post-hoc tests with emmeans.7.2 Formulating, estimating, and testing a factorial ANOVA. ![]()
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