How to control plot layout for lmerTest output results?

Question

I am using lme4 and lmerTest to run a mixed model and then use backward variable elimination (step) for my model. This seems to work well. After running the 'step' function in lmerTest, I plot the final model. The 'plot' results appear similar to ggplot2 output.

I would like to change the layout of the plot. The obvious answer is to do it manually myself creating an original plot(s) with ggplot2. If possible, I would like to simply change the layout of of the output, so that each plot (i.e. plotted dependent variable in the final model) are in their own rows.

See below code and plot to see my results. Note plot has three columns and I would like three rows. Further, I have not provided sample data (let me know if I need too!).

library(lme4)
library(lmerTest)

# Full model
Female.Survival.model.1 <- lmer(Survival.Female ~ Location + Substrate + Location:Substrate + (1|Replicate), data = Transplant.Survival, REML = TRUE)

# lmerTest - backward stepwise elimination of dependent variables
Female.Survival.model.ST <- step(Female.Survival.model.1, reduce.fixed = TRUE, reduce.random = FALSE, ddf = "Kenward-Roger" )
Female.Survival.model.ST
plot(Female.Survival.model.ST)

comments: (1) you might want to add coord_flip() if that fits in well (although it's may not be compatible with facet_wrap(); (2) can I encourage you to read these comments by Frank Harrell about stepwise procedures? — Ben Bolker
– Ben Bolker, Commented Jul 29, 2015 at 19:06

aosmith · Accepted Answer · 2015-07-29 18:09:14Z

3

The function that creates these plots is called plotLSMEANS. You can look at the code for the function via lmerTest:::plotLSMEANS. The reason to look at the code is 1) to verify that, indeed, the plots are based on ggplot2 code and 2) to see if you can figure out what needs to be changed to get what you want.

In this case, it sounds like you'd want facet_wrap to have one column instead of three. I tested with the example from the **lmerTest* function step help page, and it looks like you can simply add a new facet_wrap layer to the plot.

library(ggplot2)
plot(Female.Survival.model.ST) + 
    facet_wrap(~namesforplots, scales = "free", ncol = 1)

answered Jul 29, 2015 at 18:09

aosmith

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Comments

alku · Accepted Answer · 2015-07-29 19:44:04Z

1

Try this: plot(difflsmeans(Female.Survival.model.ST$model, test.effs = "Location "))

answered Jul 29, 2015 at 19:44

alku

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