First, a quasi-experimental design requires a comparisons between those who were exposed to some factor versus those in a "non-equivalent control group" who did not have any exposure to the "intervention." So, that may not be the more accurate description for what you are doing.

Practically speaking, if your analysis is basically a comparison of three different groups, then a one-way ANOVA would adequate. You could do that separately for each DV, or you could combine them into a MANOVA.

If you have different level of IV (levels of LGBTQ inclusivity as mentioned by you) and more than 2 group (as the variable under study has different lavels) then ANOVA would be a suitable statistics to go for. But what are the conditions because of which you are calling it a Quasy experiment. You need to elaborate on that.

David L Morgan Pradeep Gupta

Thank you both for your responses!

I think I’ve got my terminology wrong in terms of describing it as a ‘quasi’ design. I thought it would be this since I’m unable to manipulate the IV of ‘inclusivity of sex education received‘ since it is drawing on the participants’ personal experiences and not conditions I have set up and put different participants into. Participants will self assign to these groups depending on how they respond to the initial questionnaire within the study so, hypothetically a score between 0-10 on these questions may mean a low level of inclusivity and they would be categorised in this group. - I will have 3 levels of the IV which I will then want to compare each to the DV within my analyses.

I hope this clarifies it a bit more? Are you able to advise the type of design this would be if not quasi?

Thank you for your help!