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ffmanova (version 1.1.1)

Fifty-Fifty MANOVA

Description

General linear modeling with multiple responses (MANCOVA). An overall p-value for each model term is calculated by the 50-50 MANOVA method by Langsrud (2002) , which handles collinear responses. Rotation testing, described by Langsrud (2005) , is used to compute adjusted single response p-values according to familywise error rates and false discovery rates (FDR). The approach to FDR is described in the appendix of Moen et al. (2005) . Unbalanced designs are handled by Type II sums of squares as argued in Langsrud (2003) . Furthermore, the Type II philosophy is extended to continuous design variables as described in Langsrud et al. (2007) . This means that the method is invariant to scale changes and that common pitfalls are avoided.

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Install

install.packages('ffmanova')

Monthly Downloads

753

Version

1.1.1

License

GPL-2

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Maintainer

Oyvind Langsrud

Last Published

March 28th, 2022

Functions in ffmanova (1.1.1)

ffAnova

Type II* Anova
fixModelMatrix

Fix the "factor" matrix of a terms object.
matlabColon

Simulate Matlab's `:'
m2c

Conversion between matrices and partitioned matrices
manova5050

Computation of 50-50 MANOVA results
adjust

Adjust a predictor matrix for the presence of another matrix
linregEst

Linear regression estimation
ffmanovatest

50-50 MANOVA testing
ffmanova

Fifty-fifty MANOVA
dressing

Dressing data
norm

Matrix norm.
print.ffmanova

Print method for ffmanova
predict.ffmanova

Predictions, mean predictions, adjusted means and linear combinations
stdize

Centering and scaling of matrices
rotationtests

Rotation testing
multiPvalues

p-values from MANOVA test statistics
multiStatistics

MANOVA test statistics
unitests

Univariate F or t testing
orth_D

Making adjusted design matrix data
x_Obj

Creation of a design matrix object
myorth

Rank and orthonormal basis
xy_Obj

Creation of a design-with-responses object
my_pValueF

F-test p-values