Finding Interaction and main effects contrasts for two-wayANOVA

 Dale,

Other than the first SAS contrast, does the following demonstrate what
your asking for?

summary(twoway)

 material temp       voltage
 1:12     50:12   Min.   : 20
 2:12     65:12   1st Qu.: 70
 3:12     80:12   Median :108
                  Mean   :106
                  3rd Qu.:142
                  Max.   :188

contrasts(twoway$material)

  2 3
1 0 0
2 1 0
3 0 1

contrasts(twoway$temp)

   65 80
50  0  0
65  1  0
80  0  1

fit <- aov(voltage ~ material*temp, data=twoway)
summary.aov(fit)

              Df Sum Sq Mean Sq F value  Pr(>F)
material       2  10684    5342    7.91  0.0020 **
temp           2  39119   19559   28.97 1.9e-07 ***
material:temp  4   9614    2403    3.56  0.0186 *
Residuals     27  18231     675
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1


# setting (partial) contrasts

contrasts(twoway$material) <- c(1,-1,0) # ignoring the second

available df

contrasts(twoway$temp) <- c(0,1,-1) # ignoring the second  
available df
contrasts(twoway$material)

  [,1]  [,2]
1    1 -0.41
2   -1 -0.41
3    0  0.82

contrasts(twoway$temp)

   [,1]  [,2]
50    0 -0.82
65    1  0.41
80   -1  0.41

summary.aov(fit, split=list(material=list('m1-m2'=1), temp=list 
('t50 -

t80'=1)))
                                 Df Sum Sq Mean Sq F value  Pr(>F)
material                          2  10684    5342    7.91 0.00198 **
  material: m1-m2                 1   3800    3800    5.63 0.02506 *
temp                              2  39119   19559   28.97 1.9e-07 ***
  temp: t50 - t80                 1  11310   11310   16.75 0.00035 ***
material:temp                     4   9614    2403    3.56 0.01861 *
  material:temp: m1-m2.t50 - t80  1   4970    4970    7.36 0.01146 *
Residuals                        27  18231     675
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

# other examples of setting contrasts
# compare m1 vs m2 and m2 vs m3

contrasts(twoway$material) <- matrix(c(1,-1,0,1,1,-2), nrow=3)
contrasts(twoway$material)

  [,1] [,2]
1    1    0
2   -1    1
3    0   -1
# compare m1 vs m2 and m1+m2 vs m3

contrasts(twoway$material) <- matrix(c(1,-1,0,1,1,-2), nrow=3)
contrasts(twoway$material)

  [,1] [,2]
1    1    1
2   -1    1
3    0   -2

I'm not sure if 'summary.aov' is the only lm-family summary method  
with
the split argument.

DaveT.
*************************************
Silviculture Data Analyst
Ontario Forest Research Institute
Ontario Ministry of Natural Resources
david.john.thompson at ontario.ca
http://ofri.mnr.gov.on.ca
*************************************

-----Original Message-----
From: Steele [mailto:dale.w.steele at gmail.com]
Sent: March 6, 2008 09:08 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Finding Interaction and main effects contrasts
for two-way ANOVA

I've tried  without success to calculate interaction and main effects
contrasts using R.  I've found the functions C(), contrasts(),
se.contrasts() and fit.contrasts() in package gmodels.  Given the url
for a small dataset and the two-way anova model below, I'd like to
reproduce the results from appended SAS code.  Thanks.  --Dale.

 ## the dataset (from Montgomery)
twoway <- read.table("http://dsteele.veryspeedy.net/sta501/ 
twoway.txt",
col.names=c('material', 'temp','voltage'),colClasses=c('factor',
'factor', 'numeric'))

 ## the model
fit <- aov(voltage ~ material*temp, data=twoway)

/* SAS code */
proc glm data=twoway;
class material temp;
model voltage = material temp material*temp;
contrast '21-22-31+32' material*temp 0 0 0 1 -1 0 -1 1 0;
estimate '21-22-31+32' material*temp 0 0 0 1 -1 0 -1 1 0;
contrast 'material1-material2' material 1 -1 0;
estimate 'material1-material2' material 1 -1 0;
contrast 'temp50 - temp80' temp 1 0 -1;
estimate 'temp50 - temp80' temp 1 0 -1;
run;