The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
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")
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.