mixedroast: Multiple Contrast Rotation Tests based on Marginal Mixed...
In daniel-gerhard/mcroast: Multiple Contrast Rotation Tests

Description Usage Arguments Details Value Author(s) References Examples

Adaption of the roast function in package limma to perform a maxT-test for fixed effects in multiple linear mixed models, controlling FWER for multiple contrasts.

1	mixedroast(formula, data = NULL, K, nrot = 9999, adjusted = TRUE)

`formula`	A formula object, analogously to lmer, with a matrix of response variables (independent subjects in rows) on the left, and design covariates + random effects on the right hand side.
`data`	A data.frame object, searching for column names in formula.
`K`	A contrast matrix (different contrasts in rows), with the same number of columns as number of parameters in the model
`nrot`	Number of Monte Carlo simulation steps
`adjusted`	logical, if TRUE single-step maxT FWER control is performed; if FALSE the comparison-wise error rate is controlled

Most of the code was taken from function roast in package limma (Bioconductor).

A list with

`Y`	The matrix of response variables
`X`	The design matrix
`statistic`	A matrix of test statistics
`pvalue`	A matrix of (adjusted) p-values
`B`	A matrix with contrast parameter estimates
`mrot`	A vector with simulated maxT statistics under H0

Daniel Gerhard

Wu, D, Lim, E, Francois Vaillant, F, Asselin-Labat, M-L, Visvader, JE, and Smyth, GK (2010). ROAST: rotation gene set tests for complex microarray experiments. Bioinformatics 26, 2176-2182.

Langsrud, O (2005). Rotation tests. Statistics and Computing 15, 53-60.

# Soils MANOVA example of package car
data("Soils", package = "car")
# Using the Group dummy variable summarizing the 2-factorial design
# Contrasts for all-pair comparison of Group levels
K <- multcomp::contrMat(table(Soils$Group), type="Tukey")
# define Block as random factor
mxr <- mixedroast(cbind(pH, N, Dens, P, Ca, Mg, K, Na, Conduc) ~ Group-1 + (1|Block), 
                  data=Soils, K=K, nrot=999)
mxr$pvalue