Analysis of factors influencing survival time of patients with heart failure Department: Mathematics and Statistics By: kruskalstat Project ID: 4635 Rating: (5.0) votes: 1Rate this project12345 Price:₦3000 Get the Complete MaterialAbstractThis paper deals with statistical analysis of some predictors influencing the survival of cardiac dysfunctional cases diagnosed in a specialized medical center with the aim of estimating major contributors of heart failure patients’ period of survival. The design of this research focused on a metropolis where some cohorts were diagnosed over a given period of time. This study used two distinct models of survival analysis to investigate the incidence of heart failure and estimate the relevant factors of the survival of victims. The Kaplan Meier model and the Cox regression model were adopted. The output of the paper was obtained using the SPSS 23.0 to estimate the model parameters yielding the outcomes indicating that the overtime, the potency of surviving heart attack is drastically poor. The survivor function connotes the chances that a patient survives from the time of beginning to sometimes beyond the period. The survival experience of the population under investigation is estimated by the Kaplan Meier method. In the paper, Kaplan Meier estimated the probability of surviving the attack within the cohort group at the point of diagnosis as 0.42 in 2013 which really decayed in 2019 to 0.006 depicting the reduced chances of the patients surviving the attack over the period Cox regression analysis uncovered that using a 0.05, the p-values estimated that age, hypertension and blood pressure contribute to the surviving heart dysfunction inpatients being diagnosed. ...Preview Download Preview +Other Mathematics and Statistics project topics and materials you might be interested in»Statistical Quality Control of Premier Soap in Soap Manufacturing Industry ( A Case Study of PZ Cusson PLC Aba Abia State)»Statistical analysis of students’ height and weight (case study of federal polytechnic Nekede, Owerri, Imo state) »Statistical analysis of unemployment rate among age groups and geographical locations in Nigeria»Statistical analysis of the problems associated with skill acquisition in Nigeria (a case study of male tailors in Imo state)»Application of linear programming technique to profit maximization in the production of soap (a case study of Promotex industrial and chemical company limited, Nnewi, Anambra state) »Statistical analysis of foster care and adoption rate in Abia state (a case study of motherless babies home Ahiaeke, Umuahia)»Determination of nutritional status of children within the ages of four (4) to ten (10) years using their body mass index (BMI)»Determinant of foreign direct investment in Nigeria and its effect on Nigerian economy: an empirical analysis»Econometrics analysis of gross national income on consumption expenditure of federal republic of Nigeria between (2011)»Time series analysis on marriage registration in Ilorin, Kwara state»Statistical analysis on impact of parental hood on academic performance»Application of multiple queuing model in evaluating the efficiency of service in UBA bank»Statistical analysis of factors affecting crime in Imo state»Statistical study of the queuing pattern at the antinatal division of Federal Medical Center FMC Owerri Imo state»A statistical analysis of coal production in Nigeria - a case study of Nigeria coal corporation from 2000-2009