README.md

In aberrance: Detect Aberrant Behavior in Test Data

aberrance

The aberrance package contains a collection of functions for detecting several types of aberrant behavior, including:

• Answer copying, using statistics such as the $\omega$ statistic (Wollack, 1997).
• Answer similarity, using statistics such as the $GBT$ statistic (van der Linden & Sotaridona, 2006) and the $M4$ statistic (Maynes, 2014).
• Nonparametric misfit, using statistics such as the $ZU3$ statistic (van der Flier, 1982) and the $H^T$ statistic (Sijtsma, 1986).
• Parametric misfit, using statistics such as the standardized log-likelihood statistic (Drasgow et al., 1985) and its various corrections (Bedrick, 1997; Gorney et al., 2024; Molenaar & Hoijtink, 1990; Snijders, 2001).
• Preknowledge, using statistics such as the signed likelihood ratio test statistic (Sinharay, 2017).
• Rapid guessing, using methods such as the custom threshold method (Wise et al., 2004; Wise & Kong, 2005), the normative threshold method (Wise & Ma, 2012), and the cumulative proportion correct method (Guo et al., 2016).
• Test tampering, using statistics such as the erasure detection index (Wollack et al., 2015; Wollack & Eckerly, 2017) and its corrected versions (Sinharay, 2018).

Installation

Install the released version from CRAN:

install.packages("aberrance")

Alternatively, install the development version from GitHub:

# install.packages("devtools")
devtools::install_github("kyliegorney/aberrance")

aberrance documentation built on April 4, 2025, 3:19 a.m.