Fitting Linear Probability Model and Logit to Prevalence of Hepatitis B and C Data in Donga Local Government Area of Taraba State
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Abstract
Hepatitis B and C are significant global public health concerns, responsible for a substantial burden of liver disease. The prevalence of hepatitis B and C varies widely across different populations and regions, influenced by factors such as age, sex, geographic location, and risk behaviors. This study focuses on examining the effects of age and sex on the prevalence of hepatitis B and C. By analyzing data on the presence or absence of these infections across different age categories and between sexes, we aim to identify patterns that could inform targeted public health efforts. Linear probability model and logit through generalised linear model were fitted on the data collected at the first referral hospital laboratory Donga. Results showed that both models fit the data, and significant factors are age category and the interaction of age category and sex. But it is discovered that the logit model fitted the data more with a lower value of AIC and BIC.
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