Hi,
I'm running a multilevel model using lmer. I noticed that when I only have ONE predictor modelled as fixed and random effect, the degrees of freedom for the t statistic of the predictor are based on the N of Level 2 (in my case Countries).
When I add TWO additional fixed effects, the number of degrees of freedom for the t statistic for Predictor 1 (modelled as fixed and random effect) is still based on the N of Level 2 while the degreess of freedom for Predictors 2 and Predictors 3 are based on the N of Level 1 (in my case persons)
CODE:
Model1 = lmer(Y ~ Predictor1 +
(Predictor1 + 1 |Country), data,
control = lmerControl(optimizer = "bobyqa"))
summary(Model1)
OUTPUT:
Number of obs: 45544, groups: Country, 54
t statistic of fixed effect of Predictor1 has df = 52.27
Model2 = lmer(Y ~ Predictor1 + Predictor2 + Predictor3
(Predictor1 + 1 |Country), data,
control = lmerControl(optimizer = "bobyqa"))
summary(Model2)
OUTPUT:
Number of obs: 45544, groups: Country, 54
t statistic of fixed effect of Predictor1 has df = 52.27
t statistic of fixed effect of Predictor2 has df = 44720
t statistic of fixed effect of Predictor3 has df = 44720