Corpus ID: 49364461

Comparing Methodologies for Developing an Early Warning System: Classification and Regression Tree Model versus Logistic Regression. REL 2015-077.

  title={Comparing Methodologies for Developing an Early Warning System: Classification and Regression Tree Model versus Logistic Regression. REL 2015-077.},
  author={S. Koon and Y. Petscher},
The CART results were found to be comparable to those of logistic regression, while using fewer or the same number of variables. This means that rather than complicated mathematical operations, decision trees may be used to accurately classify students as at-risk and not at-risk readers. Decision trees have been found to be easier to interpret and use by practitioners in fields where they are often used, such as health care. 
A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility
Abstract The main purpose of the present study is to use three state-of-the-art data mining techniques, namely, logistic model tree (LMT), random forest (RF), and classification and regression treeExpand
Clinical prediction rules for assisting diagnosis
Structured summary 2 Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal andExpand
Educational data mining: A tutorial for the rattle package in R
Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDMExpand
Factors Associated With Social Isolation Among the Older People in India
Requiring help in performing ADL, advancing age, and Alzheimer's disease were the likely factors for socially isolation among elderly patients in this surveyed population. Expand
Data Analytics and Decision- Making in Education: Towards the Educational Data Scientist as a Key Actor in Schools and Higher Education Institutions.
In this chapter, we outline the importance of data usage for improving policymaking (at the system level), management of educational institutions and pedagogical approaches in the classroom. WeExpand
A Guide to Developing and Evaluating a College Readiness Screener. REL 2016-169.
To improve placement accuracy, colleges that currently rely solely on placement test scores may wish to consider a broader screening tool that incorporates other student information. Expand


Using Classification and Regression Trees (CART) in SAS® Enterprise Miner TM For Applications in Public Health.
Classification and regression trees (CART) - a non-parametric methodology- were first introduced by Breiman and colleagues in 1984. In this paper they are employed using SAS® Enterprise Miner™ andExpand
An Introduction to Classification and Regression Tree (CART) Analysis
A common goal of many clinical research studies is the development of a reliable clinical decision rule, which can be used to classify new patients into clinically-important categories, and there are a number of reasons for these difficulties. Expand
Rule-Based Classification Systems Using Classification and Regression Tree (CART) Analysis
Incorporating ancillary data into image classification can increase classification accuracy and precision. Rule-based classification systems using expert systems or machine learning are aExpand
Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression
C&RT is a promising research tool for the identification of at-risk populations in public health research and outreach and is compared to a common approach to logistic regression, the stepwise selection procedure. Expand
Development and validation of a decision tree early warning score based on routine laboratory test results for the discrimination of hospital mortality in emergency medical admissions.
Evidence is provided that the results of commonly measured laboratory tests collected soon after hospital admission can be represented in a simple, paper-based EWS (LDT-EWS) to discriminate in-hospital mortality. Expand
The Predictive Validity of the Early Warning System Tool
The Early Warning System is a tool developed by the National High School Center to collect data on indicators including attendance, grade point average, course failures, and credits earned. TheseExpand
Combining non-parametric models with logistic regression: an application to motor vehicle injury data
To date, computer-intensive non-parametric modelling procedures such as classification and regression trees (CART) and multivariate adaptive regression splines (MARS) have rarely been used in theExpand
A Classification Tree Approach to the Development of Actuarial Violence Risk Assessment Tools
This work proposes a classification tree rather than a main effects regression approach for actuarial violence risk assessment tools, and suggests that by employing two decision thresholds for identifying high- and low-risk cases, the use of actuarial tools to make dichotomous risk classification decisions may be further enhanced. Expand
The process and utility of classification and regression tree methodology in nursing research
This paper presents a discussion of classification and regression tree analysis and its utility in nursing research, providing insightful understanding of complex and hierarchical relationships in an accessible and useful way to nursing and other health professions. Expand
Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis
The basic Bayesian framework must be constrained, use of the step function in computing the probability that a team would rank best or worst in a league, and implementation of a Dirichlet process prior are presented. Expand