Optimal Data Analysis
Person-Environment (PE) fit theory was used to explore the relationship between student involvement and freshman retention. Incoming freshmen (N=382) were followed longitudinally in a twowave panel study, the summer before beginning college, and again during the spring of their freshman year. Involvement levels, a variety of summer and spring preferences (Ps), and spring perceptions (Es) regarding specific aspects of their college environment were assessed. Twelve PE fit indicators were derived and compared with respect to their relationship with student involvement and retention. Results indicated that involvement was linked to some PE fit indicators. Traditional parametric statistical analyses were compared with a new, nonparametric technique, Classification Tree Analysis (CTA), to identify the most accurate classification model for use in designing potential attrition interventions. Discriminant analysis was 14% more accurate than CTA in classifying returners (97% vs. 85%), but CTA was 962% more accurate classifying dropouts (8% vs. 84%). CTA identified nine clusters— five of returners and four of dropouts, revealing that different subgroups of freshmen chose to return (and stay) for different reasons. Students’ end-of-the-year preferences appear to be more important than anticipated preferences, college perceptions, or PE fit levels
Howard Smith, Jennifer; Bryant, Fred B.; Njus, David; and Posavac, Emil J.. Here Today, Gone Tomorrow: Understanding Freshman Attrition Using Person-Environment Fit Theory. Optimal Data Analysis, 1, : 101-124, 2010. Retrieved from Loyola eCommons, Psychology: Faculty Publications and Other Works,
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