mod_fitting: A function to get the fitting information for a list of lmer...
In EricMenetre/NPL: An incomplete toolkit for the researcher in NeuroPsychoLinguistic
Description
This function takes as input a list of models and returns the AIC, BIC, log likelihood, deviance and residual degrees of freedom of each one of the lmer and glmer models. When REML is set to TRUE, the functions returns for this model the cAIC from the cAIC4 pkg. The models are then ordered according to the smallest AIC or cAIC.
Usage
1
mod_fitting(models)
Arguments
models
A list of lmer or glmer models under the form list(M1 = m1, M2 = m2, ..., Mn = mn). it is also possible to enter the data without names: c(m1, m2, m3) but this way of doing might be confusing when having many models.
EricMenetre/NPL documentation built on June 23, 2021, 2:10 p.m.
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Description
This function takes as input a list of models and returns the AIC, BIC, log likelihood, deviance and residual degrees of freedom of each one of the lmer and glmer models. When REML is set to TRUE, the functions returns for this model the cAIC from the cAIC4 pkg. The models are then ordered according to the smallest AIC or cAIC.
Usage
1 | mod_fitting(models)
|
Arguments
models |
A list of lmer or glmer models under the form list(M1 = m1, M2 = m2, ..., Mn = mn). it is also possible to enter the data without names: c(m1, m2, m3) but this way of doing might be confusing when having many models. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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