Poisson regression is one of the methods to analyze count data and, the regression parameters are usually estimated using the maximum likelihood (ML) method.However, the ML method is sensitive to multicollinearity. Multicollinearity occurs when there is linear dependency among the explanatory variables. Multicollinearity often leads to unstable maximum likelihood estimates. In this article, we developed modified jackknifed Poisson Kibria-Lukman (MJPKL) estimator to mitigate multicollinearity in the Poisson regression model. We theoretically compared the MJPKL estimator with some existing estimators and obtained the condition for the superiority of MJPKL. A simulation study and real-life application were conducted to compare the performance of the estimators. It is evident from the simulation and real-life results that the modified jackknifed Poisson K-L estimator (MJPKLE) gives better results than other estimators under some conditions. Finally, the MJPKL estimator reduces the bias of the PKL estimator and dominates every estimator considered in this article.
Hypertension arises when the blood pressure against the artery walls is very high. Blood pressure is represented with two numbers. The first number (systolic) signifies the pressure in blood vessels when the heart beats and while second number (diastolic) denotes the pressure in the vessels when the heart rests between beats. Usually hypertension is referred to as blood pressure above 130/90, and is considered severe if the pressure is above 180/120. Hypertension has been a major public health challenge in the world at large which is also the most common widespread of diseases affecting human life. Hypertension has been an important area of research due to its high prevalence and major risk factors for cardiovascular diseases. It affects mostly adults and is called a silent killer because it shows no symptom. This article examines reported cases of hypertensive patients at Akulue Memorial Hospital, Nsukka, Enugu State. The data used in this research was collected from inpatient unit of the above mentioned hospital for a period of ten years, from 2009 to 2018. A 3-way contingency table was used based on Chi-squared test of independency. The result obtained from this study show that there is an association between the three criteria tested (gender, year and type of hypertension patient suffers). Also, we observed that the type of hypertension a patient suffers from depends on gender and year of occurrence.
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