Open AccessLoglinear Modeling of Academic Performance Data
Author(s) -
Bushirat T. Bolarinwa,
Ismaila A. Bolarinwa
Publication year - 2021
Publication title -
international journal of advanced statistics and probability
Language(s) - English
Resource type - Journals
ISSN - 2307-9045
DOI - 10.14419/ijasp.v9i1.31509
Subject(s) - goodness of fit , graduation (instrument) , statistics , log linear model , statistic , mathematics , maximum likelihood , linear model , geometry
The focus of this article was to fit a hierarchical loglinear model to data on academic performance. Data on gender, university attended for B.Sc., B.Sc. and M.Sc. grades of 116 M.Sc. graduates were collected from Department of Statistics, University of Ilorin, Ilorin, Nigeria. Model estimation was carried out by iterative proportional fitting method. Likelihood ratio statistic was utilized for goodness of fit test. The final model generating class contained University, Gender, and B.Sc.*M.Sc., and in harmony with the principle of hierarchy, also contained B.Sc. and M.Sc. grades. Significant interaction was found between B.Sc. and M.Sc. grades only. All other 2-factor and all 3-factor interactions were found not to be significant. Thus, M.Sc. grade was neither associated with gender and university nor with their interaction. The likelihood ratio statistic with p-value of 0.722 suggested model adequacy. The study concluded that only B.Sc. grade was associated with M.Sc. grade obtained by students on graduation. The need to extend study to other departments in the University was recommended.