[R] transforming data glm

[Mcdonald, Grant]

Dear sir,

I am fitting a glm with default identity link:


 model<-glm(timetoacceptsecs~maleage*maletub*relweight*malemobtrue*femmobtrue)

the model is overdisperesed and plot model shows a low level of linearity of the residuals.  The overdispersion and linearity of residulas on the normal Q-Q plot is corrected well by using:


 model<-glm(log(timetoacceptsecs)~maleage*maletub*relweight*malemobtrue*femmobtrue))

Boxcox of my model also suggests that the log transformation is what i should do.

I ask how i am able to do this by changing the link function or error family of my glm and not diretly taking the log of the response variable.  

For instance:
model<-glm(log(timetoacceptsecs)~maleage*maletub*relweight*malemobtrue*femmobtrue, family=poisson))
does not improve my model in terms of overdispersion etc as much as taking the log.

Thank you