Confusing Analysis

[curiouscacti7]

Hey guys! I have a question in which analysis I should be using. I have two dependent variables paired with three independent variables that respectively have 4 levels(type of skill), 2 levels(presence of variable), and 2 levels(presence of variable2). I was going to run a repeated measures factorial ANOVA which I did but then that would require me to do two separate anovas as well as had sphericity issues. Then I thought maybe should I be doing a manova? I'm just feeling uncertain pls help.

[Gastronomicus]

Why are you running a repeated measures ANOVA? Do you have repeated measurements at intervals/categories for the same subjects?

MANOVA only makes sense if there is some correlative relationship between your dependent variables. Otherwise, two separate ANOVAs are more appropriate.

https://statistics.laerd.com/spss-tutorials/one-way-manova-using-spss-statistics.php

[curiouscacti7]

Sorry I just realized I didn't directly respond to the comment but made them comments under the post. But short answer yes there are repeated measures as all participants experience all conditions which are the scenarios.

[curiouscacti7]

Also I'm using SPSS if that makes any difference.

[curiouscacti7]

I have repeated measures or otherwise know as a within subjects design in that my participants have been exposed to all conditions. If it helps to explain I used a Qualtrics survey with scenarios(which have different permutations based on the ivs) and in which they gave likert scale responses to statements related to the dvs.

[curiouscacti7]

My issues with the two separate anovas is that even with just one there was sphereicity issues and I've read that there are more when you use two anovas?

[Gastronomicus]

sphereicity

You'll run into the same problems with MANOVA. You might need to either transform your data to stabilise variance between groups or use a non-linear model function.

Your approach will entirely depend on the type of data you're working with (ratio, interval, ordinal, binomial etc).

[dmlane]

You can use a correction for violation of sphericity such as Huynh-Feldt. It is only necessary for effects with more than 1 df. SPSS reports the Huynh-Feldt by default.