The R package aberrance contains a collection of functions for detecting several types of aberrant behavior, including:
Answer copying, using statistics such as the ω statistic (Wollack, 1997).
Answer similarity, using statistics such as the GBT statistic (van der Linden & Sotaridona, 2006) and the M4 statistic (Maynes, 2014).
Change point, using statistics such as the likelihood ratio test-based statistic, the score test-based statistic, and the Wald test-based statistic (Shao et al., 2016; Sinharay, 2016; Tu et al., 2023).
Nonparametric misfit, using statistics such as the ZU3 statistic (van der Flier, 1982) and the HT 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).