It has been an eventful month since my last post. As planned, Dr. Rosenthal and myself conducted Hierarchical Linear Modeling in the statistical program SAS. We have found very interesting results about my sample, the Madison Scouts.
Using SAS, we analyzed trajectories, or patterns, of change over time, on average, for the Madison Scouts members who were participating in my project. We were able to find significant negative linear models for all of my outcomes (resilience, general self-efficacy, marching self-efficacy, goal orientation, and flow), but even more interestingly, we were able to find significant positive curvilinear models for all of the outcomes. Curvilinears are difficult to interpret until one creates figures to see the actual curve.
After creating graphs of all my curves on excel, I was able to see the unique curves for each outcome. For each of my constructs, there is a decrease from the start of the project, then a rebound after one point. After the rebound point, the constructs increase over time until the end of the project. Even though they all show this general pattern, they are unique in that some have differing rebound points, or that some do not increase to a point higher than where they started. Each curve is interesting on its own, but together they tell me a lot about how the Drum Corps season impacted the members of the Madison Scouts psychosocially.
Using my preliminary results, we were able to write up an abstract that I submitted to the American Psychological Association in hopes to present my projects’ finding at the APA’s annual Conference. For now, I am patiently waiting for their response, as well as cleaning up drafts of the manuscript so that we can potentially get it out to possible publishers by the end of January or early February.