Logit models, the area under receiver characteristic curves, sensitivity, and specificity for Co-enrollment density in college networks dataset.

ABSTRACT: This article describes the data related to co-enrollment density (CD), a new network clustering index, that can predict persistence and graduation. The data hold the raw results and charts obtained with the algorithm for CD introduced in ``Co-Enrollment Density Predicts Engineering Students' Persistence and Graduation: College Networks and Logistic Regression Analysis.'' There are data for eight institutions that show CD as a predictor for graduation at four years, graduation at six years, and ever graduated. The files were processed using R to estimate CD at one, two, three, and four years. Logistic regression models, receiver operating characteristic curves, specificity, sensitivity, and cut-off points were estimated for each model. The R code to reproduce the metanalysis f

SUBMITTER: Huerta-Manzanilla EL 

PROVIDER: S-EPMC8573127 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature