R package WRS2. A collection of robust statistical methods based on Wilcox’ WRS functions. It implements robust t-tests (independent and dependent samples), robust ANOVA (including between-within subject designs), quantile ANOVA, robust correlation, robust mediation, and nonparametric ANCOVA models based on robust location measures.
Keywords for this software
References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Wilcox, Rand R.: Introduction to robust estimation and hypothesis testing (2017)
- Schlägel, Ulrike E.; Lewis, Mark A.: Robustness of movement models: can models bridge the gap between temporal scales of data sets and behavioural processes? (2016)
- Wilcox, Rand R.: ANCOVA: a heteroscedastic global test when there is curvature and two covariates (2016)
- Yuan, Ke-Hai; Chan, Wai; Tian, Yubin: Expectation-robust algorithm and estimating equations for means and dispersion matrix with missing data (2016)
- Wilcox, Rand: Comparing the variances of two dependent variables (2015)
- Ling, Yan; Nelson, Paul I.: Effect size for comparing two or more normal distributions based on maximal contrasts in outcomes (2014)
- Wilcox, Rand R.; Clark, Florence: Comparing robust regression lines associated with two dependent groups when there is heteroscedasticity (2014)
- Hamon, Agnès; Ycart, Bernard: Statistics for the Luria-Delbrück distribution (2012)
- Wilcox, Rand: Introduction to robust estimation and hypothesis testing (2012)