[R] lmer for two models followed by anova to compare the two models

[Lawrence Hanser]

Dear Colleagues,

I run this model:

mod1 <- lmer(x~category+subcomp+category*subcomp+(1|id),data=impchiefsrm)

obtain this summary result:

Linear mixed-effects model fit by REML
Formula: x ~ category + subcomp + category * subcomp + (1 | id)
  Data: impchiefsrm
 AIC  BIC logLik MLdeviance REMLdeviance
4102 4670  -1954       3665         3908
Random effects:
Groups   Name        Variance Std.Dev.
id       (Intercept) 0.11562  0.34003
Residual             0.22765  0.47713
number of obs: 2568, groups: id, 107


run this model (only difference is I've removed the interaction term):

mod2 <- lmer(x~category+subcomp+(1|id),data=impchiefsrm)

obtain this summary result:

Linear mixed-effects model fit by REML
Formula: x ~ category + subcomp + (1 | id)
   Data: impchiefsrm
  AIC  BIC logLik MLdeviance REMLdeviance
 3987 4151  -1966       3823         3931
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.11528  0.33953
 Residual             0.23584  0.48564
number of obs: 2568, groups: id, 107

Note that the loglik from the first model is -1954 and from the second
model loglik is -1966.

Next, to test the difference between the two models I run:

anova(mod1, mod2) and obtain this result:

Data: impchiefsrm
Models:
mod2: x ~ category + subcomp + (1 | id)
mod1: x ~ category + subcomp + category * subcomp + (1 | id)
     Df     AIC     BIC  logLik  Chisq Chi Df Pr(>Chisq)
mod2 28  3879.1  4042.9 -1911.5
mod1 97  3859.3  4426.9 -1832.7 157.72     69   6.71e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Note that in this result the logLiks are reported as -1832.7 and
-1911.5 respectively for models 1 and 2.

Now my question:

Why are the logLiks from the anova command that compares the two
models different from what was reported in the separate model results?

Thanks,

Larry