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reflectR
View on CRAN: Click
here
Download and install reflectR package within the R console
Install from CRAN:
install.packages("reflectR")
Install from Github:
library("remotes")
install_github("cran/reflectR")
Install by package version:
library("remotes")
install_version("reflectR", "2.1.3")
Attach the package and use:
library("reflectR")
Maintained by
Giuseppe Corbelli
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-05-03
Latest Update: 2024-05-03
Description:
A tool for researchers and psychologists to automatically code open-ended responses to the Cognitive Reflection Test (CRT), a widely used class of tests in cognitive science and psychology for assessing an individual's propensity to override an incorrect gut response and engage in further reflection to find a correct answer. This package facilitates the standardization of Cognitive Reflection Test responses analysis across large datasets in cognitive psychology, decision-making, and related fields. By automating the coding process, it not only reduces manual effort but also aims to reduce the variability introduced by subjective interpretation of open-ended responses, contributing to a more consistent and reliable analysis. 'reflectR' supports automatic coding and machine scoring for the original English-language version of CRT (Frederick, 2005) <doi:10.1257/089533005775196732>, as well as for CRT4 and CRT7, 4- and 7-item versions, respectively (Toplak et al., 2014) <doi:10.1080/13546783.2013.844729>, for the CRT-long version built via Item Response Theory by Primi and colleagues (2016) <doi:10.1002/bdm.1883>, and for CRT-2 by Thomson & Oppenheimer (2016) <doi:10.1017/s1930297500007622>. Note: While 'reflectR' draws inspiration from the principles and scientific literature underlying the different versions of the Cognitive Reflection Test, it has been independently developed and does not hold any affiliation with any of the original authors. The development of this package benefited significantly from the kind insight and suggestion provided by Dr. Keela Thomson, whose contribution is gratefully acknowledged. Additional gratitude is extended to Dr. Paolo Giovanni Cicirelli, Prof. Marinella Paciello, Dr. Carmela Sportelli, and Prof. Francesca D'Errico, whose contributions highlighted the significant importance and practical relevance of this construct in personality, social, and cognitive research.
How to cite:
Giuseppe Corbelli (2024). reflectR: Automatic Scoring of the Cognitive Reflection Test. R package version 2.1.3, https://cran.r-project.org/web/packages/reflectR
Previous versions and publish date:
2.0.2 (2024-05-03 15:00)
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