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In short: how to extract the different sum of squares from a mixed-effect model built using "lme" function in R (package nlme)?

In long: I am trying to finish my first experimental study. One reviewer asked me to report effect sizes for my mixed-effects model. I used mixed-effects models because I have a one-way repeated-measure design with one categorical predictor including different number of observations for each category (something the ANOVA does not like at all).

I found in Bakeman (2005) and Olejnik & Algina (2003) that generalized eta squared is particularly suited, and should be easy to compute. For that I need the sum of squares of my model. Unfortunately, as said before, I am new to this kind of statistics. I am completely struggling to understand all the posts I find on the internet, and may have missed my answer somewhere. It may even exist a different estimate of effect sizes for my design.

Nevertheles, for the moment I go on the only way I found. Would anyone know how to extract sum of squares from the model built with "lme"?

Thank you for your time.

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  • $\begingroup$ Have you tried using the aov_4() function in the afex package? It should compute generalized eta squared (ges) values. See singmann.org/… for details. $\endgroup$ Commented Aug 15, 2018 at 2:18
  • $\begingroup$ @IsabellaGhement thank you for this suggestion! I did not know this package, which sounds really convenient for multiple uses. I will take a look at it. $\endgroup$
    – Pyxel
    Commented Aug 15, 2018 at 8:53

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