Mixed ANOVA and missing data

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Antonia.98
Posts: 1
Joined: Tue Aug 26, 2025 2:01 pm

Mixed ANOVA and missing data

Post by Antonia.98 »

Hey dear community,

I´ve just recently started using jamovi as a platform to conduct statistical research, so please forgive me if my question seems a bit clueless. :grin:
I wanted to conduct a mixed ANOVA, 2 groups, 2 time points, one dependent variable. I wanted to do this for 5 variables, which are each facets (scales) of a bigger construct. I soon realized that my data did have some missing values, so some of the items on those different facets were unanswered by a few people here and there.
My first question would be: does jamovi automatically exclude the persons that have missing values from the analyses? And if so, 2., does jamovi only exclude those, who had missing values in the "pre testing" or would a person also be excluded if they had a value in the pre testing, but not in the post? 3. Is there a way to actually see the "n" that has been used for the analysis? I´ve seen the descriptive data, but understanding how many people were actually part of the ANOVA in jamovi is kind of a black box to me thus far.

I hope I could explain it properly. Thank you so much for reading and maybe an answer !

Best wishes, Antonia
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reason180
Posts: 351
Joined: Mon Jul 24, 2017 4:56 pm

Re: Mixed ANOVA and missing data

Post by reason180 »

Hi. In any repeated-measures ANOVA, including mixed ANOVA, if a participant has any missing cells, all of that participant's data is excluded from all aspect of the analysis. This applies not just to jamovi but to any stats program. (Note that there is an advanced, alternative to ANOVA that uses the available data from every participant.)
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jonathon
Posts: 2874
Joined: Fri Jan 27, 2017 10:04 am

Re: Mixed ANOVA and missing data

Post by jonathon »

The GAMLj3 module provides "mixed models" that allow you to run an analysis which might be considered "equivalent" to an RM ANOVA, however able to "cope" with missing values (i.e. doesn't need to listwise delete subjects who have some missing values).

https://gamlj.github.io/

jonathon
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