LOGANTree: Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments

Enables researchers to model log-file data from computer-based assessments using machine-learning techniques. It allows researchers to generate new knowledge by comparing the performance of three tree-based classification models (i.e., decision trees, random forest, and gradient boosting) to predict student's outcome. It also contains a set of handful functions for the analysis of the features' influence on the modeling. Data from the Climate control item from the 2012 Programme for International Student Assessment (PISA, <https://www.oecd.org/pisa/>) is available for an illustration of the package's capability. He, Q., & von Davier, M. (2015) <doi:10.1007/978-3-319-19977-1_13> Boehmke, B., & Greenwell, B. M. (2019) <doi:10.1201/9780367816377> .

Version:	0.1.1
Depends:	R (≥ 3.5.0)
Imports:	ROCR, caret, caretEnsemble, dplyr, ggplot2, rpart.plot, tibble, gbm, stats
Published:	2022-06-22
Author:	Denise Reis Costa [aut, ths], Qi Qin [aut, cre]
Maintainer:	Qi Qin <logantreeqq at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	LOGANTree results

Documentation:

Reference manual:

LOGANTree.pdf

Downloads:

Package source:	LOGANTree_0.1.1.tar.gz
Windows binaries:	r-devel: LOGANTree_0.1.1.zip, r-release: LOGANTree_0.1.1.zip, r-oldrel: LOGANTree_0.1.1.zip
macOS binaries:	r-release (arm64): LOGANTree_0.1.1.tgz, r-oldrel (arm64): LOGANTree_0.1.1.tgz, r-release (x86_64): LOGANTree_0.1.1.tgz, r-oldrel (x86_64): LOGANTree_0.1.1.tgz
Old sources:	LOGANTree archive

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