Specifying that model is logit transformed to plot backtransformed trends

I have fitted a lme model in R with a logit transformed response. I have not been able to find a direct command that does the logit transformation so I have done it manually.

logitr<-log(r/1-r)

I then use this as response in my lme model with interaction between two factors and a numerical variable.

model<-lme(logitr<-factor1*factor2*numeric,random=1|random)

Now, R obviously do not know that this model is logit transformed. How can I specify this to R?

I have without luck tried:

update(model, tran="logit")

The reason why I want to specify that the model is logit transformed is because I want to plot the backtransformed results using the function emmip in the emmeans package, showing the trends of the interaction between my variables.

Normally (if I only had factors) I would just use:

update_refgrid_model<-ref_grid(update(model, tran="logit"))

But this approach does not work when I want to use emmip to plot the trends of the interaction between a numerical variable and factors. If I specify:

emmip(update_refgrid_model, factor1~numeric|factor2, cov.reduce = range, type = "response")

then I do not get any trends plotted, only the estimate for the average level on the numerical variable.

So, how can I specify the logit transformation and plot the backtransformed trends of a lme model with factors interacting with numerical variables?