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Discriminant Analysis to Predict Graduation – Nongraduation in a Master's Degree Program in Nursing
Author(s) -
Tripp Alice,
Duffey Margery
Publication year - 1981
Publication title -
research in nursing and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 85
eISSN - 1098-240X
pISSN - 0160-6891
DOI - 10.1002/nur.4770040403
Subject(s) - graduation (instrument) , linear discriminant analysis , discriminant function analysis , analysis of variance , statistics , regression analysis , medicine , psychology , demography , clinical psychology , mathematics , geometry , sociology
Discriminant analysis was used to predict graduation and two categories of nongraduation from readily available admissions data at the University of Kansas nursing master's degree program. The traditional admissions indices, baccalaureate grade point average (GPA) and Graduate Record Examination (GRE)‐verbal and ‐quantitative scores, were used as predictors. Criterion categories were composed of 102 graduates, 103 individuals who dropped out of the program, and 65 individuals who were not accepted. The first discriminant function was, X 2 (6)=87.567, p < .0001, and extracted 98% of the variance of the discriminant space. Follow‐up procedures using one‐way ANOVA's and Scheffé multiple comparisons indicated that the baccalaureate GPA and the GRE‐verbal and ‐quantitative scores independently differentiated the graduate and dropout groups from the not‐accepted group at a statistically significant level ( p < .05). Pratical significance of the independent contribution of these variables to group differentiation, as measured by ω 2 was 22% for the baccalaureate GPA, 13% for the GRE‐verbal scores, and 10% for the GRE‐quantitative scores. Implications for future research are discussed.