linearHypothesis equivalent for ols command (rms package) in R

Question

I am trying to use "linearHypothesis" function from "car" package to test coefficients of a model estimated with "ols" from "rms" package. The function works with "lrm" objects but not with "ols" objects. Have you got any alternatives? I know that using "lm" would sort the issue but I want to use "ols" since it is easier getting clustered standard errors there.

Answer 1

You can use glht from the multcomp package.

library(rms)
library(multcomp)

d <- datadist(swiss); options(datadist="d")
fit <- ols(Fertility ~ ., data = swiss)
summary(fit)

test <- glht(fit, linfct = "Agriculture = 0")
summary(test)
# Fit: ols(formula = Fertility ~ ., data = swiss, x = TRUE)
# 
# Linear Hypotheses:
#                  Estimate Std. Error z value Pr(>|z|)  
# Agriculture == 0  -0.1721     0.0703  -2.448   0.0144 *
#   ---
#   Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1