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What does the output of dredge function show?
As @gung pointed out, the output shows the model ‘rank’ from best to worst according to AICc score; the values under each predictor column indicate the estimated coefficient for that parameter in that model. Since your “best” model is blank for all three, your summary indicates that none of the predictors improve model fit.
How to generate model selection table in dredge?
Generate a model selection table of models with combinations (subsets) of fixed effect terms in the global model, with optional rules for model inclusion.
Which is the second best model in dredge?
The second best model shows lNN to have a negative effect. No value means no effect. AIC values show that these model are not very informative. Is this interpretation correct or am I missing something? The function MuMIn::dredge simply returns a list of models with every possible combination of predictor variable.
Do you use model averaging in dredge cross?
Since the first four models have similar support (notice also that their Akaike weight, wich varies from 0 to 1, are not relatively high) I strongly suggest that you use model averaging, take a look at MuMIn::model.avg and also read Chapter 4 of Burnham & Anderson (2002). I hope this are clearly enough, but feel free to ask again
Is the interpretation of dredge-Cross is correct?
That’s not correct. dredge returns a list with every possible combination of variables, if a variable doesn’t have a value, it means it was not included in the model. For example, model 3 only has 1NN, besides intercept obviously. AIC values show that these model are not very informative. Is this interpretation correct or am I missing something?
How to get all fitted models in dredge?
The fitted model objects are not stored in the result. To get (possibly a subset of) the models, use get.models on the object returned by dredge . Another way of getting all the models is to run lapply (dredge (…, evaluate = FALSE), eval), which avoids fitting the models twice.