Question

I want to run a multiple comparisons analysis for the different variables of a model. My idea is as follows:

library(multcomp)
set.seed(123)
x1 <- gl(4,10)
x2 <- gl(5,2,40)
y <- rnorm(40)

fm1 <- lm(y ~ x1 + x2)

for(var in c('x1', 'x2'))
{
mc1 <- glht(fm1, linfct=mcp(var='Tukey'))
print(summary(mc1))
}

When I run, I get the following error:

Error en mcp2matrix(model, linfct = linfct) : 
    Variable(s) ‘var’ have been specified in ‘linfct’ but cannot be found in ‘model’! 

That is, it is not possible to use a character to specify an attribute of the mcp function.
Anyone knows a solution?

Answer 1

(Update: Make sure to see Hadley’s answer for the better way of doing this, without resorting to string-pasting. My answer will still be useful for explaining why that is harder-than-usual in this case.)

The peculiarities of mcp() require you to use the relatively brute force approach of pasting together the expression you’d like to evaluate and then passing it through eval(parse()).

The tricky bit is that mcp() interprets its first argument in a nonstandard way. Within mcp(), x1 = 'Tukey' does not (as it normally would) mean “assign a value of 'Tukey' to the argument x1“. Instead, the whole thing is interpreted as a symbolic description of the intended contrasts. (In this, it is much like more familiar formula objects such as the y ~ x1 + x2 in your lm() call).

for(var in c('x1', 'x2')) {
    # Construct a character string with the expression you'd type at the command 
    # line. For example : "mcp(x1 = 'Tukey')"
    exprString <- paste("mcp(", var, "='Tukey')")
    # eval(parse()) it to get an 'mcp' object.
    LINFCT <- eval(parse(text = exprString))
    mc1 <- glht(fm1, linfct = LINFCT)
    print(summary(mc1))
}