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- W2002912352 abstract "This study aimed to investigate predicting factors for detecting guilty individuals who committed a mock crime using a functional data analysis, to reduce an individual variation of psychophysiological data and to find weighted integration of function. Fifty-four participants (30 male, 24 female) chose either guilty condition (stealing a wallet) or innocent condition (non-crime). Skin conductance level (SCL), temperature, and pulse were measured during conducting a concealed information test. A functional logistic regression indicated that SCL and pulse were predictive variables for detecting guilty. Specifically, participants were more likely to be guilty if they showed a higher degree in SCL responding to both crime-relevant and irrelevant questions and a higher increase of pulse after the crime-relevant questions. These results suggest that SCL and pulse may predict whether a suspect is guilty or innocent and that a functional data analysis could provide more accurate prediction by excluding individual variation." @default.
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- W2002912352 date "2014-04-01" @default.
- W2002912352 modified "2023-09-24" @default.
- W2002912352 title "Predicting factors of discrimination between guilty and innocent: Using a functional data analysis" @default.
- W2002912352 doi "https://doi.org/10.1016/j.paid.2013.07.289" @default.
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