Linear mixed models (LMMs) serve as a versatile statistical framework, combining fixed effects that capture the overall trends with random effects that account for variability across subjects, ...

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population ...

Limitations of linear regression applied on ecological data -- Things are not always linear : additive modeling -- Dealing with heterogeneity -- Mixed effects modeling for nested data -- Violation of ...

In the early 1970s, statisticians had difficulty in analysing data where the random variation of the errors did not come from the bell-shaped normal distribution. Besides normality, these traditional ...