[R] Different output from lm() and lmPerm lmp() if categorical variables are included in the analysis

[Agustin Lobo]

I've found a problem when using
categorical variables in lmp() from package lmPerm

According to help(lmp): "This function will behave identically to lm()
if the following parameters are set: perm="", seq=TRUE,
center=FALSE.")
But not in the case of including categorical variables:

require(lmPerm)
set.seed(42)
testx1 <- rnorm(100,10,5)
testx2 <- c(rep("a",50),rep("b",50))
testy <- 5*testx1 + 3 + runif(100,-20,20)
test <- data.frame(x1=testx1,x2=
testx2,y=testy)
atest <- lm(y ~ x1*x2,data=test)
aptest <- lmp(y ~ x1*x2,data=test,perm = "", seqs = TRUE, center = FALSE)
summary(atest)

Call:
lm(formula = y ~ x1 * x2, data = test)
Residuals:
    Min       1Q   Median       3Q      Max
-17.1777  -9.5306  -0.9733   7.6840  22.2728

Coefficients:
        Estimate Std. Error t value Pr(>|t|)
(Intercept)  -2.0036     3.2488  -0.617    0.539
x1            5.3346     0.2861  18.646   <2e-16 ***
x2b           2.4952     5.2160   0.478    0.633
x1:x2b       -0.3833     0.4568  -0.839    0.404

summary(aptest)

Call:
lmp(formula = y ~ x1 * x2, data = test, perm = "", seqs = TRUE,
center = FALSE)

Residuals:
    Min       1Q   Median       3Q      Max
-17.1777  -9.5306  -0.9733   7.6840  22.2728

Coefficients:
   Estimate Std. Error t value Pr(>|t|)
x1       5.1429     0.2284  22.516   <2e-16 ***
x21     -1.2476     2.6080  -0.478    0.633
x1:x21   0.1917     0.2284   0.839    0.404

It looks like lmp() is internally coding dummy variables in a different way, so
lmp results are for "a" (named "1" by lmp) while lm results are for
"b" ?

 Agus