Predictive Model of Student Dropout Based on Logistic Regression

Predictive Model of Student Dropout Based on Logistic Regression

Abstract Student desertion is a phenomenon that has spread significantly in many higher education institutions in Ecuador. The objective of the research was to develop a predictive model of student dropout based on multiple binary logistic regression, with the purpose of detecting possible dropouts....

Full description

Bibliographic Details
Main Authors:	B.R. Cuji Chacha, W.L. Gavilanes López, M.B. Pérez Constante
Format:	Article
Language:	Spanish
Published:	Knowledge E 2023-11-01
Series:	ESPOCH Congresses
Subjects:	logistic regression, predictive model, desertion.
Online Access:	https://doi.org/10.18502/espoch.v3i1.14477

Similar Items

ENHANCED PREDICTION OF STUDENT DROPOUTS USING FUZZY INFERENCE SYSTEM AND LOGISTIC REGRESSION
by: A. Saranya, et al.
Published: (2016-01-01)

Factor that Affects the Students’ Performance in Mathematics Subject using Logistic Regression
by: Norwaziah Mahmud, et al.
Published: (2024-03-01)

Use of Logistic Regression for Understanding and Prediction of Customer Churn in Telecommunications
by: Jan Manďák, et al.
Published: (2019-06-01)

Prediction model of agricultural water quality based on optimized logistic regression algorithm
by: RongLi Gai, et al.
Published: (2023-02-01)

Logistic regression models /
by: 290126 Hilbe, Joseph M.
Published: (2009)

Prediction of diabetes using logistic regression and ensemble techniques
by: Priyanka Rajendra, et al.
Published: (2021-01-01)

Random forest versus logistic regression: a large-scale benchmark experiment
by: Raphael Couronné, et al.
Published: (2018-07-01)

Random State Initialized Logistic Regression for Improved Heart Attack Prediction
by: Kevyn Alifian Hernanda Wibowo, et al.
Published: (2023-12-01)

A comparative study of logistic regression based machine learning techniques for prediction of early virological suppression in antiretroviral initiating HIV patients
by: Kuteesa R. Bisaso, et al.
Published: (2018-09-01)

Scenario-Based Real-Time Flood Prediction with Logistic Regression
by: Jaeyeong Lee, et al.
Published: (2021-04-01)

Predicting company growth using logistic regression and neural networks
by: Marijana Zekić-Sušac, et al.
Published: (2016-12-01)

Predicting Diabetes Disease Occurrence Using Logistic Regression: An Early Detection Approach
by: Ahmad Abdalrada, et al.
Published: (2024-01-01)

Predictive market segmentation model: An application of logistic regression model and CHAID procedure
by: Soldić-Aleksić Jasna
Published: (2009-01-01)

Comparing the predictive performance of a decision tree with logistic regression for oral cavity cancer mortality: A retrospective study
by: K Sevvanthi, et al.
Published: (2023-01-01)

Prediction of Tuberculosis Using a Logistic Regression Model
by: Kiarash Ghazvini, et al.
Published: (2019-09-01)

Pavement Distress Initiation Prediction by Time-Lag Analysis and Logistic Regression
by: Hao Liu, et al.
Published: (2022-11-01)

The Prediction Models for High-Risk Population of Stroke Based on Logistic Regressive Analysis and Lightgbm Algorithm Separately
by: Yicheng Xue, et al.
Published: (2022-05-01)

Application of topography and logistic regression in forest type spatial prediction
by: Fariba Ghanbari, et al.
Published: (2011-03-01)

Logistic regression analysis in Bronchopulmonary Dysplasia /
by: 238494 Kavitha Samannamuthaliar
Published: (2008)

Prediction of Deterioration Level of Heritage Buildings Using a Logistic Regression Model
by: Si Chen, et al.
Published: (2023-04-01)

Robust Diagnostics In Logistic Regression Model
by: Ariffin @ Mat Zin, Syaiba Balqish
Published: (2010)

Enrollment management: Development of prediction model based on logistic regression
by: Gerasimović Milica, et al.
Published: (2016-01-01)

Predicting Crash Rate Using Logistic Quantile Regression With Bounded Outcomes
by: Xu, Xuecai, et al.
Published: (2018)

Influence of Logistic Regression Models For Prediction and Analysis of Diabetes Risk Factors
by: Yufri Isnaini Rochmat Maulana, et al.
Published: (2018-07-01)

Testing and Validating Two Morphological Flare Predictors by Logistic Regression Machine Learning
by: M. B. Korsós, et al.
Published: (2021-01-01)

Analysis and Prediction of MOOC Learners’ Dropout Behavior
by: Zengxiao Chi, et al.
Published: (2023-01-01)

Categorical Data Analysis - Logistic Regression
by: Shengping Yang, et al.
Published: (2014-07-01)

Logistic regression analysis in Bronchopulmonary Dysplasia [electronic resource] /
by: 238494 Kavitha Samannamuthaliar
Published: (2008)

Logistic regression: A simple primer
by: Ankita Pal
Published: (2021-01-01)

Logistic regression : a self-learning text /
by: 343793 Kleinbaum, David G.
Published: (1994)

Common pitfalls in statistical analysis: Logistic regression
by: Priya Ranganathan, et al.
Published: (2017-01-01)

Robust Estimators of Logistic Regression with Problems Multicollinearity or Outliers Values.
by: Fadhil Abbul Abbas AL- Aabdi, et al.
Published: (2014-12-01)

Prediction of Coal Mine Pressure Hazard Based on Logistic Regression and Adagrad Algorithm—A Case Study of C Coal Mine
by: Bobin Zhu, et al.
Published: (2023-11-01)

Factors affecting the grade point average students of FMIPA Universitas Negeri Padang with binary logistic regression model
by: Irma Surya Anisa, et al.
Published: (2022-09-01)

PEMODELAN RISIKO PENYAKIT PNEUMONIA PADA BALITA DI PROVINSI JAWA TIMUR DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION
by: EVI NOVIYANTARI FATIMAH, et al.
Published: (2015-05-01)

Predicting Type Two Diabetes and Determination of Effectiveness of Risk Factors Applying Logistic Regression Model
by: M Aram-Ahmaddi, et al.
Published: (2014-03-01)

Certifiable Unlearning Pipelines for Logistic Regression: An Experimental Study
by: Ananth Mahadevan, et al.
Published: (2022-06-01)

Predicting the Safety Climate in Construction Sites of Saudi Arabia: A Bootstrapped Multiple Ordinal Logistic Regression Modeling Approach
by: Anas A. Makki, et al.
Published: (2021-02-01)

A Logistic Regression Model for Predicting Axillary Lymph Node Metastases in Early Breast Carcinoma Patients
by: Jiaqing Zhang, et al.
Published: (2012-07-01)

Land Use Change Modelling Using Logistic Regression, Random Forest and Additive Logistic Regression in Kubu Raya Regency, West Kalimantan
by: Alfa Nugraha Pradana, et al.
Published: (2023-12-01)