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allisonhorst.github.io | ||
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kgoldfeld.github.io
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| | | | | Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR). | |
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juliasilge.com
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| | | | | A data science blog | |
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indrajeetpatil.github.io
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| | | | | [AI summary] This article documents the ggbetweenstats R package, demonstrating how to create publication-ready statistical plots with customizable tests including parametric, non-parametric, robust, and Bayes Factor analyses. | |
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thraxil.org
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| | | [AI summary] The author describes porting the Perl CGI::Application module to Python to create a cleaner way for writing independent CGI applications. | ||
