Dear R users,
I am having a problem with interpreting "anova" results of a linear mixed
effects model.
The data I am analyzing is from study that was set up as a randomized
block design with two factors at two levels. The model is:
m1 <- lme(Y~A*B, random = ~1|Block)
The design is comple
On 11-01-20 12:24 PM, Iannone, Basil wrote:
> Dear R users,
>
> I am having a problem with interpreting "anova" results of a linear mixed
> effects model.
>
> The data I am analyzing is from study that was set up as a randomized
> block design with two factors at two levels. The model is:
>
>
Basil,
I think that the issue is how lme (and R generally) parameterizes
factorial models. The "marginal" anova fits each effect after the
others. That does not produce what SAS calls type III sums of squares
unless the model has no interactions or you use the "sum to zero"
parameterization
Phillip and Ben,
Thanks a bunch. I now understand why sequential and marginal results are not
the same, although I have to read up a little on the "contrast" that Ben
mentioned.
Thanks for the clarification.
On Thu, Jan 20, 2011 at 12:51 PM, Phillip Chapman <
pchap...@stat.colostate.edu> wrote:
