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