Hi all,
I'm having trouble with the model generating 'dredge' function in the MuMIn
'Multi-model Inference' package.
Here's the script:
globalmodel<- glm(TB~lat+protocol+tested+
streams+goats+hay+cattle+deer,
family="binomial")
chat<- deviance(globalmodel)/59 #There we 59 residual degrees of freedom in
this global model.
models<- dredge(globalmodel, beta=FALSE, evaluate=TRUE, rank="AICc",
chat=chat, fixed=NULL, trace=FALSE)
And the error message is:
Error in UseMethod("logLik") :
no applicable method for 'logLik' applied to an object of class "logical"
I have trawled the literature and it seems to be ok to use a binary GLM as
the global model - could this be the problem? The variables are a mix of
binary and continuous data.
Any thoughts?
Thanks,
Cat
Error message in dredge function (MuMIn package) used with binary GLM
2 messages · Cat Cowie, Kamil Bartoń
'rank' should be "QAICc". AICc does not have argument 'chat', hence the error. kamil CatCowie wrote
Hi all,
I'm having trouble with the model generating 'dredge' function in the
MuMIn
'Multi-model Inference' package.
Here's the script:
globalmodel<- glm(TB~lat+protocol+tested+
streams+goats+hay+cattle+deer,
family="binomial")
chat<- deviance(globalmodel)/59 #There we 59 residual degrees of freedom
in
this global model.
models<- dredge(globalmodel, beta=FALSE, evaluate=TRUE, rank="AICc",
chat=chat, fixed=NULL, trace=FALSE)
And the error message is:
Error in UseMethod("logLik") :
no applicable method for 'logLik' applied to an object of class
"logical"
I have trawled the literature and it seems to be ok to use a binary GLM as
the global model - could this be the problem? The variables are a mix of
binary and continuous data.
Any thoughts?
Thanks,
Cat
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