Comparative Study on Logit and Probit Models in the Prediction of Broncho-Pulmonary Dysplasia Status of Infants

Description

– Comparative Study on Logit and Probit Models in the Prediction of Broncho-Pulmonary Dysplasia Status of Infants –

Download Comparative Study on Logit and Probit Models in the Prediction of Broncho-Pulmonary Dysplasia Status of Infants. Medicine and Surgery students who are writing their projects can get this material to aid their research work.

Abstract

Broncho Pulmonary Dysplasia (BPD) is a form of chronic lung disease that develops in preterm neonates treated with oxygen and positive-pressure ventilation. The disease affects premature babies and contributes to their morbidity and mortality.

This research seeks to fit and compare the predictive powers of Logistic Regression (Logit) Modeland Probability Regression (Probit) Model in tracking infants’ BPD status using gender and weights at two different time intervals.

The data used for the analysis were samples of 50 infants drawn from an underlying population of children with low birth weight (g) from Ahmadu Bello University Teaching Hospital Zaria.

Introduction

The understanding of purpose of statistical science will play important roles to start a research of this kind. Usman (2016), in Bivariate and Multivariate Statistical Analysis, refers Multivariate statistical analysis as multiple advanced techniques for checking relationships among multiple variables at the same time.

Researchers use multivariate techniques in a study that involve more than one response variable (phenomenon of interest) and more than one explanatory variable (also known as a predictor) or both.

The statistical methods comes into play either when we have a medical theory to test or when we have a relationship in mind that has some importance in medical decision or policy analysis in public health.

According to Northway (1967), Broncho-Pulmonary Dysplasia (BPD)is a chronic lung disorder of infants and children and was first described in 1967.

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