lsmMat function

Contrast Matrix for LS Means

Function determines appropriate contrast matrix for computing the LS Means of each factor level of one or multiple fixed effects variables.

lsmMat(obj, var = NULL, quiet = FALSE)

Arguments

• obj: (VCA) object
• var: (character) string specifyig the fixed effects variable for which the LS Means generating matrices should be computed
• quiet: (logical) TRUE = will suppress any warning, which will be issued otherwise

Returns

(matrix) where each row corresponds to a LS Means generating contrast for each factor level of one or multiple fixed effects variable(s)

Details

This functions implements the 5 rules given in the documentation of SAS PROC GLM for computing the LS Means.#' The LS Means correspond to marginal means adjusted for bias introduced by unbalancedness.

Examples

## Not run:

data(dataEP05A2_1)
fit1 <- anovaMM(y~day/run, dataEP05A2_1)

VCA:::lsmMat(fit1, "day")       # function not exported
VCA:::lsmMat(fit1, "run")
VCA:::lsmMat(fit1)                      # is equal to listing all fixed terms

# a more complex and unbalanced model
data(VCAdata1)
datS1 <- VCAdata1[VCAdata1$sample == 1, ]
set.seed(42)
datS1ub <- datS1[-sample(1:nrow(datS1))[1:25],]
fit2 <- anovaMM(y~(lot+device)/day/(run), datS1ub)
VCA:::lsmMat(fit2, c("lot", "device"))
## End(Not run)

Author(s)

Andre Schutzenmeister andre.schuetzenmeister@roche.com