Sorry for this very basic question. I've trawled through previous pages and cannot quite find a case that corresponds to our situation. 320 individuals rated two types of films. The rating was provided on a 1-11 scale.There are many films of each type. In short the DV is a continuous variable. 20 individuals have a particular disease that we now consider of interest. We would like to examine the effect of the disease on the rating. We conducted a 2-way repeated measures ANOVA, using 'situation type' as a within-subject factor, and 'disease status' as a between-subject factor, using SPSS. The design is obviously unbalanced with more observations in the healthy group. The data appeared to be normally distributed. Levine test suggested equality of variance. Does that mean it is appropriate to use ANOVA for this analysis?


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Keep in mind that ANOVA is just a particular form of linear regression. So ask yourself whether having different numbers of observations between 2 groups would invalidate a linear regression. It wouldn't.

Having different numbers in your 2 groups would affect the precision of associated regression-coefficient estimates. With only 20 individuals in your disease group you thus might not have enough power to detect a difference unless it's large.

If the underlying assumptions of linear regression/ANOVA are met, as they seem to be in your case, then there is no inherent problem in having different numbers of cases in your groups. I don't use SPSS, but I suspect that it handles this situation correctly.

One final warning: the above assumes that your choice to analyze disease status was made without having seen a disease-associated difference in the results first. If you base analyses on results of peeking at the data, then you are violating assumptions underlying statistical testing.


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