[R] Change in R**2 for block entry regression

[Chuck Cleland]

David Kaplan wrote:
> Hi all,
> 
> I'm demonstrating a block entry regression using R for my regression 
> class.  For each block, I get the R**2 and the associated F.  I do this 
> with separate regressions adding the next block in and then get the 
> results by writing separate summary() statements for each regression. 
> Is there a more convenient way to do this and also to get the change in 
> R**2 and associated F test for the change?
> 
> Thanks in advance.
> 
> David

  I'm not sure this is the best approach, but you might start with the
data frame returned by applying anova() to several models and extend
that to include the squared multiple correlation and increments:

  mod.0 <- lm(breaks ~ 1, data = warpbreaks)
  mod.1 <- lm(breaks ~ 1 + wool, data = warpbreaks)
  mod.2 <- lm(breaks ~ 1 + wool + tension, data = warpbreaks)
  mod.3 <- lm(breaks ~ 1 + wool * tension, data = warpbreaks)
  BlockRegSum <- anova(mod.0, mod.1, mod.2, mod.3)
  BlockRegSum$R2 <- 1 - (BlockRegSum$RSS / BlockRegSum$RSS[1])
  BlockRegSum$IncR2 <- c(NA, diff(BlockRegSum$R2))
  BlockRegSum$R2[1] <- NA

  BlockRegSum

Analysis of Variance Table

Model 1: breaks ~ 1
Model 2: breaks ~ 1 + wool
Model 3: breaks ~ 1 + wool + tension
Model 4: breaks ~ 1 + wool * tension
  Res.Df    RSS Df Sum of Sq      F    Pr(>F)        R2     IncR2
1     53 9232.8
2     52 8782.1  1     450.7 3.7653       0.1 0.0488114 0.0488114
3     50 6747.9  2    2034.3 8.4980 0.0006926       0.3       0.2
4     48 5745.1  2    1002.8 4.1891 0.0210442       0.4       0.1

>  BlockRegSum$R2
[1]         NA 0.04881141 0.26914067 0.37775086

>  BlockRegSum$IncR2
[1]         NA 0.04881141 0.22032926 0.10861019

>  summary(mod.1)$r.squared
[1] 0.04881141

>  summary(mod.2)$r.squared
[1] 0.2691407

>  summary(mod.3)$r.squared
[1] 0.3777509

-- 
Chuck Cleland, Ph.D.
NDRI, Inc.
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