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[table_head]
[th_column]Título:[/th_column]
[th_column]Cycle-Breaking Acceleration for Support Vector Regression. Neurocomputing. 72 (7-9), 1398-1406.[/th_column]
[/table_head]
[table_body]
[table_row]
[row_column]Autor:[/row_column]
[row_column]Barbero, A., & Dorronsoro, J.R.[/row_column]
[/table_row]
[table_row]
[row_column]Año:[/row_column]
[row_column]2011[/row_column]
[/table_row]
[table_row]
[row_column]Enlace:[/row_column]
[row_column]http://www.sciencedirect.com/science/article/pii/S0925231211002426 [/row_column]
[/table_row]
[/table]
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[panel-header]
Abstract
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[panel-content]The present work analyses the predictive validity of measures provided by several available self-report and indirect measurement instruments to assess risk propensity (RP) and proposes a measurement instrument using the Implicit Association Test: the IAT of Risk Propensity Self-Concept (IAT-RPSC), an adaptation of the prior IAT-RP of Dislich et al. Study 1 analysed the relationship between IAT-RPSC scores and several RP self-report measures. Participants’ risk-taking behaviour in a natural setting was also assessed, analyzing the predictive validity of the IAT-RPSC scores on risk-taking behaviour compared with the self-report measures. Study 2 analysed the predictive validity of the IAT-RPSC scores in comparison with other indirect measures. Results of these studies showed that the IAT-RPSC scores exhibited good reliability and were positively correlated to several self-report and indirect measures, providing evidence for convergent validity. Most importantly, the IAT-RPSC scores predicted risk-taking behaviour in a natural setting with real consequences above and beyond all other self-report and indirect measures analysed. [/panel-content]
[/panel]
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