MVLM package is used to fit linear models with a multivariate
outcome. It utilizes the asymptotic null distribution of the multivariate
linear model test statistic to compute p-values (McArtor et al., under
review). It therefore alleviates the need to use approximate p-values based
Wilks Lambda, Pillai's Trace, the Hotelling-Lawley Trace, and Roy's Greatest
To access this package's tutorial, type the following line into the console:
There is one primary function that comprises this package:
There is one primary functions that comprise this package:
mvlm, which regresses a multivariate outcome onto a set of
predictors. Standard functions like
predict can be called on a
Davies, R. B. (1980). The Distribution of a Linear Combination of chi-square Random Variables. Journal of the Royal Statistical Society. Series C (Applied Statistics), 29(3), 323-333.
Duchesne, P., & De Micheaux, P.L. (2010). Computing the distribution of quadratic forms: Further comparisons between the Liu-Tang-Zhang approximation and exact methods. Computational Statistics and Data Analysis, 54(4), 858-862.
McArtor, D. B., Grasman, R. P. P. P., Lubke, G. H., & Bergeman, C. S. (under review). The asymptotic null distribution of the multivariate linear model test statistic. Manuscript submitted for publication.
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