Hi,
The errors terms of this LMM example is heteroskedastic and almost certainly serially correlated:
if (!require("pacman")) install.packages("pacman")
pacman::p_load(lme4)
library(gapminder)
fit.lmm <- lmer( log(lifeExp) ~ log(pop) + log(gdpPercap) +
(1|year) + (1|country), data = gapminder)
plot(fit.lmm)
Is there a way to deal with heteroskedasticity, serial correlation & cross-sectional dependence in linear mixed models?
Regards,
Amir Najafi | PhD Candidate (Political Economy)
University of Technology Sydney
amir.najafi at student.uts.edu.au<mailto:amir.najafi at student.uts.edu.au>