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What is the appropriate way to report results for linear mixed model based on the "test of fixed effects" table in SPSS?

Is it just (F=xxx, p=xxx)?

This isn't my data but this is an image I found of the output table I am talking about: http://www.ats.ucla.edu/stat/spss/faq/test11.gif

enter image description here

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  • $\begingroup$ and the parameter estimates... I'm pretty sure they're t tests, not F tests. Just report the fixed effects like you would in linear regression. $\endgroup$ Commented Mar 15, 2015 at 1:04
  • $\begingroup$ Can you paste in the output you are referring to? $\endgroup$ Commented Mar 15, 2015 at 1:12
  • $\begingroup$ @gung Sure, I just found an image online of a table (I cant figure out how to add my own) $\endgroup$
    – Jazz
    Commented Mar 24, 2015 at 14:05
  • $\begingroup$ Hi @gung thanks for inserting the table for me, but that table was just included per your request. I was wondering would the correct way to report this example data set for diet be (F=10.1, p=0.004)? I am not sure what you mean by the parameter estimates Patrick because I don't have a table reporting that in my output. Thank you! $\endgroup$
    – Jazz
    Commented Mar 24, 2015 at 18:47
  • $\begingroup$ Hi @PatrickCoulombe I am not sure what you mean by the parameter estimates because I don't have a table reporting that in my output. Thank you! $\endgroup$
    – Jazz
    Commented Mar 26, 2015 at 12:00

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It depends on how you want to report it. AFAIK, there is no APA format for reporting LMMs.

Based on this reference, the author chose to report F and p values alone. For example, he states:

The “Tests of Fixed Effects” table, Table 15.6, shows that grade (F=12.9, p=0.002) and stdTest (F=25.6, p<0.0005) each have a significant effect on a student’s reading score difference, but treatment (F=1.2, p=0.289) does not.

As you can see, he reported it as (F=25.6, p<0.0005) ignoring adding more details for the F value.

Your second option is to report it the same way F value is reported on APA style

F (numerator_df, denominator_df) = F_value, p = ...
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