`termMeans`

is a utility function designed to calculate
means for the levels of factor(s) for any term
in a multivariate linear model.

`termMeans(mod, term, label.factors=FALSE, abbrev.levels=FALSE)`

mod

An mlm model object

term

A character string indicating a given term in the model. All factors in the term must be included in the model, even if they are in the model data frame.

label.factors

If true, the rownames for each row in the result include the name(s) of the factor(s) involved, followed by the level values. Otherwise, the rownames include only the levels of the factor(s), with multiple factors separated by ':'

abbrev.levels

Either a logical or an integer, specifying whether the levels values
of the factors in the `term`

are to be abbreviated in
constructing the rownames. An integer specifies the minimum length
of the abbreviation for each factor in the term.

Returns a matrix whose columns correspond to the response variables
in the model and whose rows correspond to the levels of the factor(s)
in the `term`

.

# NOT RUN { factors <- expand.grid(A=factor(1:3),B=factor(1:2),C=factor(1:2)) n <- nrow(factors) responses <-data.frame(Y1=10+round(10*rnorm(n)),Y2=10+round(10*rnorm(n))) test <- data.frame(factors, responses) mod <- lm(cbind(Y1,Y2) ~ A*B, data=test) termMeans(mod, "A") termMeans(mod, "A:B") termMeans(mod, "A:B", label.factors=TRUE) # } # NOT RUN { termMeans(mod, "A:B:C") # generates an error # } # NOT RUN { plastic.mod <- lm(cbind(tear, gloss, opacity) ~ rate*additive, data=Plastic) colors = c("red", "darkblue", "darkgreen", "brown") heplot(plastic.mod, col=colors, cex=1.25) # add means for interaction term intMeans <- termMeans(plastic.mod, 'rate:additive', abbrev=2) points(intMeans[,1], intMeans[,2], pch=18, cex=1.2, col="brown") text(intMeans[,1], intMeans[,2], rownames(intMeans), adj=c(0.5,1), col="brown") # }