Thank you in advance for your time and help!! I’m working with data with 70 participants that completed an intervention. Participants completed surveys before and after the intervention (so pre and post data). There was missing data, so we used Mice in R to impute 50 datasets. How would I test for differences in scores from pre to post test? I thought it would be an Repeated Measures Anova given it is the same subjects and two-times. Even though a paired t-test could be sufficient, the RM ANOVA felt more appropriate because it is more robust and we are working with multiply imputed datasets. However, I’ve also read online that a mixed effects model could be appropriate. The mixed effects model equation I think would be appropriate is below.
What would be the most appropriate test in this situation? Just to simply see if there were significant changes in the outcome variable from pre to post test? Thank you so much!!
mixedeffects <- with(midsobject, lmer(outcome ~ 1 + Time + (1|Participant_ID))
mixedeffects.pool <- pool(mixedeffects)
summary(mixedeffects.pool)e
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