Model Regresi Cox Untuk Data Masa Studi (Studi Kasus: Data Masa Studi Mahasiswa Fakultas Teknik Universitas Bangka Belitung)

Ineu Sulistiana, Elyas Kustiawan, Ririn Amelia
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Abstract

Student study time is the time needed by students to complete their education, which starts from the time they enter college until they are declared graduated or have completed their study period. In the study period data, survival time observations were only carried out partially or not until the failure event. In other words, termination occurs until the observation deadline. This termination occurred due to several factors that allegedly influenced the student's study period. Using study period data for students of the Faculty of Engineering, University of Bangka Belitung, class of 2015/2016, this study used the Kaplan Meier Estimation to see the survival function of each factor causing the length of study period graphically and the Log Rank Test statistically. Meanwhile, to look at the factors that determine the length of a student's study period, researchers used the Cox Regression and Maximum Likelihood Estimation (MLE) models to find the best model. The results of the data analysis show that there are differences in the survival function in each category for all variables graphically, while the statistical comparison of the results of the estimation of the survival function curve based on gender and organizational status is not significantly different. The results of the analysis also show that the proportional hazard assumption is fulfilled through the cumulative hazard log so that categorical variables can be used in the Cox Regression model. Based on the results of the likelihood estimation, the variables that have a significant effect on the study period of Engineering Faculty students are majors and GPA variables. Furthermore, from the interpretation of the model parameters, it is obtained that the Hazard Ratio (HR) value for the study period of Mechanical, Mining and Electrical Engineering students is faster than that of Civil Engineering students, while students with GPA ≥ 3.00 have a shorter study period than students with GPA < 3.00.
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学习阶段数据的 Cox 回归模型(案例研究:班加勿里洞大学工程学院学生的学习阶段数据)
学生学习时间是指学生完成学业所需的时间,从进入大学开始,直到宣布毕业或完成学业为止。在学习期数据中,生存时间观测只进行了部分,或直到失败事件发生时才进行。换句话说,在观察截止日期之前,观察都是终止的。这种终止发生的原因据称是影响学生学习期的几个因素。本研究使用邦加勿里洞大学工程学院2015/2016级学生的学习时间数据,使用卡普兰-梅尔估计法(Kaplan Meier Estimation)从图形上观察造成学习时间长短的各因素的生存函数,并使用对数秩检验法(Log Rank Test)进行统计。同时,为了研究决定学生学习时间长短的因素,研究人员使用了考克斯回归和最大似然估计(MLE)模型来寻找最佳模型。数据分析结果表明,从图形上看,各类变量的生存函数都存在差异,而基于性别和组织状况的生存函数曲线估计结果的统计比较没有明显差异。分析结果还表明,通过累积危险对数,比例危险假设得到了满足,因此分类变量可以用于 Cox 回归模型。根据似然估计的结果,对工学院学生学习时间有显著影响的变量是专业和 GPA 变量。此外,通过对模型参数的解释,可以得出机械工程、采矿工程和电气工程专业学生学习时间的危险比(HR)值快于土木工程专业学生,而 GPA≥3.00 的学生学习时间短于 GPA<3.00 的学生。
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