![]() ![]() By default, AIC c is used to rank the models and obtain model weights, although any other information criteria can be used. For a complete list of functions, use library (help 'MuMIn'). The code runs fine (I guess), but in the results, I have this: Global model call: lmer(formula = formula, data = data) require (MuMIn) ddredge (LM.1) print (d) coefficients (d) Obtain summary information of all models to get parameter estimates summary (model.avg (d)) I know that either all models can be averaged (full model averaging) or just a subset of them (conditional averaging). Since several variables are collinear I use the subsetting function of dredge to avoid correlated variables. ![]() ![]() I am trying to MuMIn::dredge linear mixed-effect models lme4::lmer with categorical/continuous variables, the code is as follows: # Selection of variables of interest 0 I am trying to run variable selection on Poisson mixed-effect models using glmer () and dredge (). ![]()
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