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Paper Details

Non-Linear Regression Models for Heart Attack Data – An Empirical Comparison

Non-Linear Regression Models for Heart Attack Data – An Empirical Comparison

V. Vallinayagam, S. Prathap, P. Venkatesan

Journal Title:
Abstract


Non linear regression is a popular statistical tool that has been used successfully in different areas of research. The Cox proportional hazard model has achieved widespread use in the analysis of time-to-event data with censoring and covariates. The covariates may change their values over time. A frailty model is a random effects model for time variables, where the random effect (the frailty) has a multiplicative effect on the hazard. It can be used for univariate (independent) failure times, i.e., to describe the influence of unobserved covariates in a proportional hazards model. The aim of this paper is to compare the performance of Cox proportional hazard model, Cox time dependent model and Frailty model using Heart attack data. The result shows that Cox time dependent model is better than other models.

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