welchADF
Welch-James Statistic for Robust Hypothesis Testing under Heterocedasticity and Non-Normality
Implementation of Johansen's general formulation of Welch-James's statistic with Approximate Degrees of Freedom, which makes it suitable for testing any linear hypothesis concerning cell means in univariate and multivariate mixed model designs when the data pose non-normality and non-homogeneous variance. Some improvements, namely trimmed means and Winsorized variances, and bootstrapping for calculating an empirical critical value, have been added to the classical formulation. The code departs from a previous SAS implementation by L.M. Lix and H.J. Keselman, available at http://supp.apa.org/psycarticles/supplemental/met_13_2_110/SAS_Program.pdf and published in Keselman, H.J., Wilcox, R.R., and Lix, L.M. (2003) doi:10.1111/1469-8986.00060.
- Version0.3.2
- R versionunknown
- LicenseLGPL (≥ 3)
- Needs compilation?No
- welchADF citation info
- Last release09/08/2019
Documentation
Team
Pablo J. Villacorta
Insights
Last 30 days
This package has been downloaded 164 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.
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Last 365 days
This package has been downloaded 2,228 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jul 21, 2024 with 70 downloads.
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Dependencies
- Imports1 package
- Suggests1 package