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Abstract:
This study aims to evaluate the accuracy
and effectiveness of a statistical model in predicting the incidence of
neonatal jaundice. The research identifies the primary factors influencing the
onset of jaundice by analyzing data from newborn infants. Additionally, the
study determines the relative importance of the variables associated with the
likelihood of jaundice in neonates and develops a discriminant function capable
of classifying affected newborns into two categories: normal and abnormal. The
study produced several important findings. Most of the variables demonstrated
statistical significance at a level below 0.05, indicating that they play a
critical role in distinguishing between the two groups, apart from gestational
age, which was found to be statistically non-significant. Using discriminant
analysis, the model correctly classified 83.7% of the normal cases and 90.0% of
the abnormal cases. The overall correct classification rate for the sample was
87.7%, suggesting that the model successfully classified 87.7% of all
observations. This result reflects a high level of model performance and
provides strong evidence of its overall predictive efficiency.
Keywords:
Jaundice, Discriminant Analysis,
Discriminant Function, Latent Root, Model Classification, Relative Importance.
