R help - Mar 2005 - Baffled by drop1: Please ignore previous request!

My apologies to the list for sending this without adequate research. I have
found my answer; please ignore! Thanks.

I've been experimenting with drop1 for my biostatistics class, to obtain the
so-called Type III sums of squares. I am fully aware of the deficiencies of
this method, however I feel that the students should be familiar with it.
What I find baffling is that when applied to a fully balanced design, you
obtain different sums of squares. I've used this for several years in Splus
and R and never encountered this before. Am I off my rocker? I have read the
help files and remain clueless. Thanks for any advice.
> replications(Wt~Sex*Par.trt, data=tmp1)
$Sex
[1] 22

$Par.trt
[1] 22

$"Sex:Par.trt"
   Par.trt
Sex  N  S
  F 11 11
  M 11 11
> summary(tmp2<-aov(Wt~Sex*Par.trt, data=tmp1))
            Df Sum Sq Mean Sq F value    Pr(>F)
Sex          1 215600  215600 31.5367 1.638e-06 ***
Par.trt      1   7127    7127  1.0425    0.3134
Sex:Par.trt  1  19236   19236  2.8138    0.1013
Residuals   40 273459    6836
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` '
1
> drop1(tmp2, ~., test="F")
Single term deletions

Model:
Wt ~ Sex * Par.trt
            Df Sum of Sq    RSS    AIC F value    Pr(F)
<none>                   273459    392
Sex          1     53018 326477    398  7.7552 0.008144 **
Par.trt      1      1473 274932    391  0.2154 0.645067
Sex:Par.trt  1     19236 292695    393  2.8138 0.101256
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` '
1
> 
=================================================================George W.
Gilchrist                        Email #1: gwgilc at wm.edu
Department of Biology, Box 8795          Email #2: kitesci at cox.net
College of William & Mary                    Phone: (757) 221-7751
Williamsburg, VA 23187-8795                    Fax: (757) 221-6483
http://gwgilc.people.wm.edu/