Likelihood Ratio Test for non-nested mixed-effect-model comparison
Hi all, I need to compare two mixed-effects-models that would explain a dependent variable by means of two completely different sets of fixed factors (my random intercept is the same in both models). I understand that the anova() cannot be used to perform a comparison via LRTest in my case, because my models are non-nested. Thus, I would take the model with the lowest AIC (o BIC) value, but I am worried about the statistical significance, so I would prefer a LRTest and the related p-value (as provided by anova() for nested models) to support my model selection. My problem is that I don't know how to compare two non-nested mixed-effect-models via a LRTest. Any suggestion? Thank you in advance. Francesco
*Francesco SIGONA* Electronics engineer Piazza Filippo Muratore 73100 - Lecce - Italy <https://maps.google.com/maps?q=40.331002,18.156462> tel.: +39 0832 335006 fax.: +39 0832 335007 ============================================================ *Center for Interdisciplinary Research on Language (CRIL) <http://www.cril.unisalento.it> & Cognitive Neuroscience of Language and Speech Sciences Lab (CNLSS) * *Dipartimento di Studi umanistici Universit? del Salento * ============================================================ *Laboratorio Diffuso di Ricerca Interdisciplinare Applicata alla Medicina (DReAM) *