Plotting estimates (fixed effects) of a linear mixed-model

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Dan Hallatt
Dan Hallatt el 25 de Jul. de 2019
Editada: Dan Hallatt el 29 de Jul. de 2022
I am familiar with standard linear regression (non-nested) where, after employing fitresult = fitlm(domain,range,'poly1'), you can use plot(fitresult) to plot the fitted linear line with also dotted lines for the confidence bounds of that fit over the domain specified within the fit.
I am now interested in fitting the data to a linear mixed-effects model, by using fitresult = fitlme(HLM_Table,'response ~ predictor + (1|cluster)'), but I cannot find any documentation about plotting the fitted linear regression (fixed coefficients). I have found equivalent documentaruon for plotting residuals and the like, but nothing at all about plotting the actual fitted model. I could do this manually by extracting the fitted fixed coefficients and plotting a line with these over the respective domain, but I am wondering if there is a built in function such as the plot(fitresult) that I used with standard linear regression?
  2 comentarios
Lea Kerciku
Lea Kerciku el 19 de Jun. de 2022
Hi, could you share your solution on how you plotted the fitted model in the end? My statistics are not so strong and I am having the same issue. Thank you.
Dan Hallatt
Dan Hallatt el 29 de Jul. de 2022
Editada: Dan Hallatt el 29 de Jul. de 2022
Hi Lea, I'm quite sorry.. I'm pretty far removed from this and it would honestly take quite a bit of work to dig up this work years ago.
If I have some time in the next while I can post a solution, but I doubt I'll be able to help.
I hope you've found a solution in the meantime!

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the cyclist
the cyclist el 25 de Jul. de 2019
Editada: the cyclist el 7 de En. de 2020
I could find no mention in the documentation of the LinearMixedModel class that there is an equivalent object function or method. I think you'll have to construct it.
  1 comentario
Dan Hallatt
Dan Hallatt el 7 de En. de 2020
I just realized that I forgot to respond to this but I wanted to say thanks! I agree and this is what I ended up doing.

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