lsmMat: Contrast Matrix for LS Means

In VCA: Variance Component Analysis

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.

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

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.

Value

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

Author(s)

Andre Schutzenmeister [e-mail]

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)

VCA documentation built on Sept. 7, 2022, 5:07 p.m.