Parametric Regression Models of Survival Analysis

2012 ◽  
pp. 93-143
2019 ◽  
Vol 9 (1) ◽  
pp. 01
Author(s):  
Novita Eka Chandra ◽  
Siti Alfiatur Rohmaniah

Timely graduation of students can be used as an indicator to show the quality of a university. Students are said to graduate on time if they have a short study period of 4 years. The duration of the study of students varies because it is influenced by several factors. The purpose of this study is to determine the factors that have a significant effect on the duration of student studies. The factors studied included gender, GPA, school origin, joining the organization and working in college. The method used in this study is survival analysis. Survival analysis in this study used Log-normal and Weibull, parametric regression models. From the two models, it was found that the GPA and organizational factors significantly influence the duration of student studies. Next, to determine the best model is determined based on the minimum AIC value. Based on the comparison of the two models, the parametric Weibull model has a minimum AIC value, so this model is the best model. Based on HR values ??obtained by students who have a higher GPA and are more active in graduating faster or can be said to have fewer studies. Keywords: survival, regression, parametric, time of study.


2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Asokan Mulayath Variyath ◽  
P. G. Sankaran

Proportional hazard regression models are widely used in survival analysis to understand and exploit the relationship between survival time and covariates. For left censored survival times, reversed hazard rate functions are more appropriate. In this paper, we develop a parametric proportional hazard rates model using an inverted Weibull distribution. The estimation and construction of confidence intervals for the parameters are discussed. We assess the performance of the proposed procedure based on a large number of Monte Carlo simulations. We illustrate the proposed method using a real case example.


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