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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")

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Version

Install

install.packages('aberrance')

Monthly Downloads

258

Version

0.2.1

License

GPL (>= 3)

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Maintainer

Kylie Gorney

Last Published

March 7th, 2025

Functions in aberrance (0.2.1)

detect_pm

Detect parametric misfit
detect_nm

Detect nonparametric misfit
aberrance-package

aberrance: Detect Aberrant Behavior in Test Data
sim

Simulate data
detect_tt

Detect test tampering
detect_as

Detect answer similarity
detect_pk

Detect preknowledge
detect_ac

Detect answer copying
detect_rg

Detect rapid guessing