Hi all,

Based on what I've read about likelihood ratio tests, if I am to compare two
models, one model has to be nested within the other model. For instance:

model1 <- lmer (DV ~ IV1 + IV2 + (1|random_effect), data=data)
model2 <- lmer (DV ~ IV1 + (1|random_effect), data=data)
anova(model1, model2).

However, I have a study where the fixed predictor has 3 levels (say, level1,
level2, and level3). and I fit a model as the following:

M1 <- lmer (DV ~ IV + (1|random_effect), data=data)

Now, I pool level2 and level3 together to form level2_3, hence resulting in
a new fixed predictor IV_NEW that has only two levels: level1 and level2_3.
My question then is: is the new model (M2, shown below) considered to be
nested within the model shown above (M1)? And can I use likelihood ratio
test to compare M1 and M2?

M2 <- lmer (DV ~ IV_NEW + (1|random_effect), data=data)

Thank you in advance for your help!

	[[alternative HTML version deleted]]


