Indrajeet Patil

Indrajeet Patil

7 packages on CRAN

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Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It is targeted primarily at behavioral sciences community to provide a one-line code to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports only the most common types of statistical tests: parametric, nonparametric, robust, and bayesian versions of t-test/anova, correlation analyses, contingency table analysis, and regression analyses.

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Collection of functions to run statistical tests across all combinations of multiple grouping variables.

ipmisc

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Provides functions needed for data cleaning and formatting and forms data cleaning and wrangling backend for the following packages: 'ggstatsplot', 'groupedstats', 'pairwiseComparisons', and 'statsExpressions'.

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Multiple pairwise comparison tests on tidy data for one-way analysis of variance for both between-subjects and within-subjects designs. Currently, it supports only the most common types of statistical analyses and tests: parametric (Welch's and Student's t-test), nonparametric (Durbin-Conover test and Dwass-Steel-Crichtlow-Fligner test), robust (Yuen<e2><80><99>s trimmed means test).

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Statistical processing backend for 'ggstatsplot', this package creates expressions with details from statistical tests. Currently, it supports only the most common types of statistical tests: parametric, nonparametric, robust, and bayesian versions of t-test/anova, correlation analyses, contingency table analysis, and meta-analysis.

insight

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A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.

parameters

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Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see support list of insight; L<c3><bc>decke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).