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I found this answer by Ben Bolker to a post and it is really helpful (How to plot random intercept and slope in a mixed model with multiple predictors?). However, if my model looks more like this: /n mod <- lmer(resp ~ pred1 + pred2 + factor(pred3) + (1|RF1),data=d) and I also want to plot the factor's influence on the response keeping the other two constant, how would I create the nd dataframe instead? Also, how would I go about plotting random slopes? Thank you very much in advance!

EDIT: Ben, thank you very much for the answer and I apologize, of course it makes sense to give a reproducible example. So, the first question: how can I plot the influence of a predictor keeping the others constant (as described in your answer to the above linked question) if I have a factor variable in my model?

Here is my example data: https://www.dropbox.com/s/ytlocw868fsnpu7/realdatasample.csv?dl=0, please treat confidentially :).

So the model would be:

moddata <- lmer(meanQUALNEW ~ meanDBH + meanCRRATIO + richn_tar + (1|region),data=realdatasample)

From what I understand, the example given in the link above is about constructing a plot for one predictor while keeping the other constant and then vice versa and taking into account the random effect. But how do I expand that code to account for three variables and especially if it is a factor? The second question: How can I visualize the random slopes in a model like this?

moddata1 <- lmer(meanQUALNEW ~ meanDBH + meanCRRATIO + richn_tar + (richn_tar-1|region),data=realdatasample)

As far as I understand, the packages visreg and effects provide ways to visualize the fixed part of such models in the accepted way (change in one predictor keeping others constant). But they don't work (as far as I know) for nice visualizations of the random effects variance components. I realize that there is probably a lot of information about this out there, but I like the clear code example from above very much and would like to understand how to do these things "by hand". Thanks so much for any help!

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TheFaScient
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    (1) any chance of a reproducible example (you could modify the example at the linked question to produce one)? (2) Could you clarify what you mean about plotting random slopes? The model you propose above doesn't have random slopes, only random intercepts. Are you referring to a different model (in which case you should state it/give an example)? – Ben Bolker Jan 26 '15 at 13:50
  • Hi Ben, thanks a lot for the comment, I have edited the question and hope it's more clear now. – TheFaScient Jan 30 '15 at 11:35

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