

 

Dear R-users, 

 

To obtain the percentage of deviance explained when fitting a gam model using the mgcv library is straightforward:

 

summary(object.gam) $dev.expl

 

or alternatively, using the deviance (deviance(object.gam)) of the null and the fitted models, and then using 1 minus the quotient of deviances. 

 

However, when a gamm (generalizad aditive mixed model) is fitted,  the deviance is not displayed, and only the logLik of the underlying lme model can be derived (logLik(objetct.gamm$lme)), which is not enough to derive the percentage deviance explained because the logLik for the saturated model is not available. 

Any suggestions on how to obtain the deviance explained when a gamm is fitted when the typical default gauusian model is fitted? Or alternavely, are the R^2 derived from a gam model and a gamm model comparable?

 

Thanks a lot in advance,

Berta 

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