lsmMat: Contrast Matrix for LS Means.

Description Usage Arguments Details Value Author(s) Examples

Description

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

Usage

1
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 andre.schuetzenmeister@roche.com

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
## 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)


Search within the VCA package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.