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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<-update(ref_grid(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?

Ditlev Reventlow
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  • Note that `update()` doesn't do anything in `update_refgrid_model<-update(ref_grid(model, tran="logit"))` because the parentheses are in the wrong place. It should be `update_refgrid_model<-update(ref_grid(model), tran="logit")`. That said, the result is the same because `ref_grid(model, tran="logit")` is enough -- in recent updates, a lot of things get passed to `update()` automagically. – Russ Lenth Jun 02 '20 at 14:43

1 Answers1

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You don't update the model object, you update the reference grid:

rg = update(ref_grid(model, cov.reduce = range), tran = "logit")
emmip(rg, factor1~numeric|factor2, type = "response")

It is possible to update a model with other things, just not the transformation; that is in the update method for emmGrid objects.

Update

Here's an example showing how it works 

require(emmeans)
## Loading required package: emmeans

foo = transform(fiber, p = (strength - 25)/25)
foo.lm = lm(log(p/(1-p)) ~ machine*diameter, data = foo)

emm = emmeans(foo.lm, ~diameter|machine, 
              tran = "logit", at = list(diameter = 15:32))
## Warning in ref_grid(object, ...): There are unevaluated constants in the response formula
## Auto-detection of the response transformation may be incorrect

emmip(emm, machine ~ diameter)


emmip(emm, machine ~ diameter, type = "r")

Created on 2020-06-02 by the reprex package (v0.3.0)

Russ Lenth
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  • Thank you @RussLenth. Sorry, I meant to specify that I tried update(refgrid()) (have edited the question now). I have now solved the initial problem with the logit transformation, since I found out that there were many packages that allows a direct logit specification (e.g. gmodels). And using these, R understands that the lme model is logit transformed. However, problem was not solved there. When I attempt the backtransformation, only the slopes are backtransformed, meaning that the backtransformed trends are linear. Isn't it possible to plot the actual backtransformed pattern? – Ditlev Reventlow Jun 02 '20 at 09:58
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    If you plot only 2 points (min and max, as implied by `cov.reduce = range`), you get a straight line. Instead, use `at = list(numeric = c(...))` – Russ Lenth Jun 02 '20 at 13:38
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    See my updated answer. The warning message comes from the fact that it found "log" in the response but couldn't parse the transformation correctly. It doesn't matter because it is overridden by 'tran' – Russ Lenth Jun 02 '20 at 13:56