在 R 中，您可以手动设置 lm() 或 Anova() 的自由度吗？

Question

I am replicating SPSS code in R that runs several Type 3 ANOVAs. In SPSS you can specify specific contrasts in an ANOVA (eg, compare level 2 v level 4 in this 5-level variable). The resulting ANOVA tables return a test where the degrees of freedom are equal to the full sample, rather than the sample that is just concentrated in those two levels.

In R, I use the command below to run an ANOVA comparing those two levels but the resulting Residuals DF is based on the subsample of only those two levels rather than the full sample. Is there a way I can manually set the DF in either the lm() or Anova() function to avoid this issue? Or is there a way to specify contrasts that uses the full sample DF?

Anova(lm(DV ~ FiveLevelFactor, data = data, type = 3, subset = FiveLevelFactor == "2" | FiveLevelFactor == "4"))

Answer 1

How about using the linearHypothesis() function from the car package:

library(car)
data(Ornstein)

mod <- lm(interlocks ~ log(assets) + sector + nation, data=Ornstein)
linearHypothesis(mod, "nationUK = nationUS")
# Linear hypothesis test
# 
# Hypothesis:
#   nationUK - nationUS = 0
# 
# Model 1: restricted model
# Model 2: interlocks ~ log(assets) + sector + nation
# 
#   Res.Df   RSS Df Sum of Sq      F Pr(>F)
# 1    235 29829                           
# 2    234 29690  1    138.36 1.0904 0.2975