marginal vs sequential results of lme
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:
m1 <- lme(Y~A*B, random = ~1|Block)
The design is completely balanced and no data are missing. When I run a
sequential anova I get a p-value = 0.02 for factor B. When I run a
marginal anova (specified by "type = "marginal""), I get a p-value = 0.29
for factor B. The model summary ("summary (m1)" ) agrees with the marginal
test and shows a p-value = 0.29 for factor B. Further when I graph values
of Y against levels of B, I see no difference.
I thought that sequential and marginal anovas should produce the same
results when the design is balanced. Can someone please explain to me why
the results of the "anova(m1)" differ from the results of "anova(m1, type
= "marginal")" and "summary(m1)."
Thanks for your help,
Haven't spent a lot of time thinking this through, but I'm guessing that the problem is with the interaction term. Can you give a reproducible example (to save me the trouble of making one up)?