I'm trying to understand the role of Athletes Commission in a sport governing body. I collected quantitative and qualitative data to get the perspective of two different hierarchical level of participants - current active athletes (Surveys) and members of Athletes Commission - whom are retired athletes(Interviews).
Even though all the participants are athletes (active or retired) - I'm confused if they can be treated as samples from the same population.
Due to this, I got even more confused if my research can be considered "Convergent MM Design - If I can continue analyzing my data separately and than merge them in interpretation by comparing the two different hierarchical perspectives.
I would really appreciate, if anyone with MMR experience can help me regarding this.
Convergent designs can be quite difficult to implement in situations such as this because the survey results are typically expressed as statistical relationships while the the qualitative results are typically expressed as themes. Because there is no standard way to compare statistical and thematic results, convergent designs are actually quite rare in practice, no matter how appealing they are on a theoretical basis.
if you can't find a way to make a direct comparison between your two sets of results, you might consider switching to a complementary design, where each component of the project makes a contribution to a composite set of conclusions. I have attached a paper where I discuss this distinction.
Article Commentary—After Triangulation, What Next?
David L Morgan Dear Professor thank you very much. Your article gave a better understanding. Really appreciated.
Dear Daulina,
Maybe you could try to convert all your data in percentage of something that could make sense for you and analyse using non parametric tests.
I don't believe that there is a test to fit quantitative and qualitive data together and you can't use a mixed model test or a parametric test in your data.
Cheers
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