I am running a two-way anova test using Anova from car package. My data looks like this:
> head(x)
Type Bin Score
1 0 SI 2.120
2 0 R 2.246
3 0 R 2.246
4 0 R 2.511
5 0 R 2.420
6 0 R 2.270
> summary(x)
Type Bin Score
0:906 I : 68 Min. :1.202
1:258 R :1570 1st Qu.:2.000
2:346 SI: 328 Median :2.280
3:436 Mean :2.299
4: 20 3rd Qu.:2.622
Max. :3.233
> lapply(x,class)
$Type
[1] "factor"
$Bin
[1] "factor"
$Score
[1] "numeric"
With an unbalanced design as follows:
> table(x$Type,x$Bin)
I R SI
0 42 702 162
1 6 190 62
2 2 296 48
3 18 362 56
4 0 20 0
So I after much research, I ended up using Anova from car package with Type III SS method. Here is how I am conducting the test:
> Anova(lm(Score ~ Bin * Type, data=x, contrasts=list(Bin=contr.sum, Type=contr.sum)),singular.ok = TRUE, type=3)
With results as follows:
Note: model has aliased coefficients
sums of squares computed by model comparison
Anova Table (Type III tests)
Response: Score
Sum Sq Df F values Pr(>F)
Bin 0.000 0
Type 2.081 3 4.3875 0.004381 **
Bin:Type 5.494 6 5.7927 5.42e-06 ***
Residuals 308.700 1953
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Can someone please help me understand:
1) This particular line from the results? Why might the SS and DF be zero for Bin?
Sum Sq Df F values Pr(>F)
Bin 0.000 0
2) How this particular model still has aliased coefficients if Bin is not even being included in the final result?
Note: model has aliased coefficients
sums of squares computed by model comparison
3) Is there a better way to conduct this test in R?
