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Zero-one augmented beta and zero-inflated discrete models with heterogeneous dispersion for the analysis of student academic performance

机译:零散增强模型和零膨胀离散模型,具有异构扩散,用于分析学生的学习成绩

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The purpose of this work is to present suitable statistical methods to study the performance of undergraduate students based on the incidence/proportion of failed courses/subjects. Three approaches are considered: first, the proportion of failed subjects is modeled considering a zero-one augmented beta distribution; second, discrete models are used to model the probability of failing subjects with logit link; third, incidence is modeled using regression for count data with log link and the logarithm of the total number of subjects as an offset. Zero-inflated versions are used to account for the excess of zeros in the data when appropriate and we also considered the heterogeneous dispersion parameter, when applicable. Overall, the zero-inflated negative binomial and zero inflated beta-binomial models, with regression on the mean and the dispersion parameters, present good measures of goodness of fit to the data. The database consists of records of Engineering major students who entered the State University of Campinas, Brazil, from 2000 to 2005. Entrance exam scores and demographic variables as well as socio-economic status are considered as covariates in the models.
机译:这项工作的目的是根据失败的课程/科目的发生率/比例,提出合适的统计方法来研究本科生的表现。考虑了三种方法:首先,考虑零扩展的β分布对失败对象的比例进行建模;其次,使用离散模型对具有logit链接的对象失败的概率进行建模。第三,使用对数链接的计数数据和对象总数的对数作为偏移量,对回归数据使用回归模型。适当时,零膨胀版本用于说明数据中零的多余部分,并且在适用时我们还考虑了异构色散参数。总体而言,零膨胀负二项式和零膨胀β二项式模型(均值和分散参数回归)提供了拟合数据的良好度量。该数据库由2000年至2005年进入巴西坎皮纳斯州立大学的工程专业学生的记录组成。入学考试成绩和人口统计学变量以及社会经济状况被视为模型中的协变量。

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