VCA (version 1.3.1)

lsmMat: Contrast Matrix for LS Means.

Description

Function determines appropriate contrast matrix for computing the LS Means of each factor level of one or multiple fixed effects variables. This functions implements the 5 rules given in the documentation of SAS PROC GLM for computing the LS Means.

Usage

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

Value

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

Details

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)