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kassambara
rstatix:Pipe-Friendly Framework for Basic Statistical Tests
Provides a simple and intuitive pipe-friendly framework, coherent with the 'tidyverse' design philosophy, for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. The output of each test is automatically transformed into a tidy data frame to facilitate visualization. Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix. Functions are also included to facilitate the analysis of factorial experiments, including purely 'within-Ss' designs (repeated measures), purely 'between-Ss' designs, and mixed 'within-and-between-Ss' designs. It's also possible to compute several effect size metrics, including "eta squared" for ANOVA, "Cohen's d" for t-test and 'Cramer V' for the association between categorical variables. The package contains helper functions for identifying univariate and multivariate outliers, assessing normality and homogeneity of variances.
Maintained by Alboukadel Kassambara. Last updated 2 years ago.
458 stars 15.27 score 11k scripts 432 dependents
cmstatr
cmstatr:Statistical Methods for Composite Material Data
An implementation of the statistical methods commonly used for advanced composite materials in aerospace applications. This package focuses on calculating basis values (lower tolerance bounds) for material strength properties, as well as performing the associated diagnostic tests. This package provides functions for calculating basis values assuming several different distributions, as well as providing functions for non-parametric methods of computing basis values. Functions are also provided for testing the hypothesis that there is no difference between strength and modulus data from an alternate sample and that from a "qualification" or "baseline" sample. For a discussion of these statistical methods and their use, see the Composite Materials Handbook, Volume 1 (2012, ISBN: 978-0-7680-7811-4). Additional details about this package are available in the paper by Kloppenborg (2020, <doi:10.21105/joss.02265>).
Maintained by Stefan Kloppenborg. Last updated 15 days ago.
composite-material-datadatamaterials-sciencestatistical-analysisstatistics
4 stars 6.36 score 23 scripts
jinkim3
kim:A Toolkit for Behavioral Scientists
A collection of functions for analyzing data typically collected or used by behavioral scientists. Examples of the functions include a function that compares groups in a factorial experimental design, a function that conducts two-way analysis of variance (ANOVA), and a function that cleans a data set generated by Qualtrics surveys. Some of the functions will require installing additional package(s). Such packages and other references are cited within the section describing the relevant functions. Many functions in this package rely heavily on these two popular R packages: Dowle et al. (2021) <https://CRAN.R-project.org/package=data.table>. Wickham et al. (2021) <https://CRAN.R-project.org/package=ggplot2>.
Maintained by Jin Kim. Last updated 1 months ago.
7 stars 4.62 score 3 scripts