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 ...

The new approach recognizes the discrete nature of ignition counts by using generalized linear and generalized linear mixed models for the first time in this type of application. It includes careful ...

XINYU ZHANG, GUOHUA ZOU, HUA LIANG, Model averaging and weight choice in linear mixed-effects models, Biometrika, Vol. 101, No. 1 (MARCH 2014), pp. 205-218 Free online reading for over 10 million ...

Joseph G. Ibrahim, Ming-Hui Chen, Stuart R. Lipsitz, Missing Responses in Generalised Linear Mixed Models When the Missing Data Mechanism is Nonignorable, Biometrika, Vol. 88, No. 2 (Jun., 2001), pp.