IDEAS home Printed from https://ideas.repec.org/a/eee/jcjust/v80y2022ics0047235220302749.html
   My bibliography  Save this article

Incremental validity of the Psychopathy Checklist-Revised above and beyond the diagnosis of antisocial personality disorder regarding recidivism in sexual offenders

Author

Listed:
  • Yoon, Dahlnym
  • Eher, Reinhard
  • Mokros, Andreas

Abstract

The diagnostic criteria of the Antisocial Personality Disorder (ASPD) overlaps greatly with the Lifestyle and Antisocial facets of the Hare Psychopathy Checklist-Revised (PCL-R), whereas the Interpersonal and Affective facets seem to differentiate between antisocial and psychopathic offenders. Previous studies investigated either the ASPD diagnosis or psychopathy measured with the PCL-R, but not the combination of both in sexual offenders. The present study tested three hypotheses that PCL-R scores are incrementally predictive above and beyond the ASPD diagnosis regarding general recidivism, non-sexual violent recidivism, and sexual recidivism.

Suggested Citation

  • Yoon, Dahlnym & Eher, Reinhard & Mokros, Andreas, 2022. "Incremental validity of the Psychopathy Checklist-Revised above and beyond the diagnosis of antisocial personality disorder regarding recidivism in sexual offenders," Journal of Criminal Justice, Elsevier, vol. 80(C).
  • Handle: RePEc:eee:jcjust:v:80:y:2022:i:c:s0047235220302749
    DOI: 10.1016/j.jcrimjus.2020.101780
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047235220302749
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jcrimjus.2020.101780?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mahmood Zafar & Khan Salahuddin, 2009. "On the Use of K-Fold Cross-Validation to Choose Cutoff Values and Assess the Performance of Predictive Models in Stepwise Regression," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-21, July.
    2. Patrick J. Heagerty & Yingye Zheng, 2005. "Survival Model Predictive Accuracy and ROC Curves," Biometrics, The International Biometric Society, vol. 61(1), pages 92-105, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Salekin, Randall T. & Andershed, Henrik, 2022. "Psychopathic personality, and its dimensions in the prediction of negative outcomes: Do they offer incremental value above and beyond common risk factors? Introduction to the special section," Journal of Criminal Justice, Elsevier, vol. 80(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jessica M. Mc Lay & Roy Lay-Yee & Barry J. Milne & Peter Davis, 2015. "Regression-Style Models for Parameter Estimation in Dynamic Microsimulation: An Empirical Performance Assessment," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 83-127.
    2. Robin Van Oirbeek & Emmanuel Lesaffre, 2018. "An Investigation of the Discriminatory Ability of the Clustering Effect of the Frailty Survival Model," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 6(3), pages 87-98, April.
    3. Yuanjia Wang & Huaihou Chen & Runze Li & Naihua Duan & Roberto Lewis-Fernández, 2011. "Prediction-Based Structured Variable Selection through the Receiver Operating Characteristic Curves," Biometrics, The International Biometric Society, vol. 67(3), pages 896-905, September.
    4. Kevin He & Yue Wang & Xiang Zhou & Han Xu & Can Huang, 2019. "An improved variable selection procedure for adaptive Lasso in high-dimensional survival analysis," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 569-585, July.
    5. Weining Shen & Jing Ning & Ying Yuan, 2015. "A direct method to evaluate the time-dependent predictive accuracy for biomarkers," Biometrics, The International Biometric Society, vol. 71(2), pages 439-449, June.
    6. Shanshan Li & Yang Ning, 2015. "Estimation of covariate‐specific time‐dependent ROC curves in the presence of missing biomarkers," Biometrics, The International Biometric Society, vol. 71(3), pages 666-676, September.
    7. Hannes Kröger & Rasmus Hoffmann, 2018. "The association between CVD-related biomarkers and mortality in the Health and Retirement Survey," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(62), pages 1933-2002.
    8. Yingye Zheng & Tianxi Cai & Ziding Feng, 2006. "Application of the Time-Dependent ROC Curves for Prognostic Accuracy with Multiple Biomarkers," Biometrics, The International Biometric Society, vol. 62(1), pages 279-287, March.
    9. C. Jason Liang & Patrick J. Heagerty, 2017. "Rejoinder to discussions on: A risk-based measure of time-varying prognostic discrimination for survival models," Biometrics, The International Biometric Society, vol. 73(3), pages 745-748, September.
    10. C. Jason Liang & Patrick J. Heagerty, 2017. "A risk-based measure of time-varying prognostic discrimination for survival models," Biometrics, The International Biometric Society, vol. 73(3), pages 725-734, September.
    11. Baccini, Leonardo & Koenig-Archibugi, Mathias, 2014. "Why do states commit to international labor standards?: interdependent ratification of core ILO conventions, 1948-2009," LSE Research Online Documents on Economics 57665, London School of Economics and Political Science, LSE Library.
    12. Yingye Zheng & Patrick J. Heagerty, 2007. "Prospective Accuracy for Longitudinal Markers," Biometrics, The International Biometric Society, vol. 63(2), pages 332-341, June.
    13. van Geloven, N. & He, Y. & Zwinderman, A.H. & Putter, H., 2021. "Estimation of incident dynamic AUC in practice," Computational Statistics & Data Analysis, Elsevier, vol. 154(C).
    14. Kröger, Hannes & Hoffmann, Rasmus, 2018. "The Association between Cvd-Related Biomarkers and Mortality in the Health and Retirement Survey," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 38, pages 1933-2002.
    15. Mei-Cheng Wang & Shanshan Li, 2012. "Bivariate Marker Measurements and ROC Analysis," Biometrics, The International Biometric Society, vol. 68(4), pages 1207-1218, December.
    16. Olivier Lopez & Xavier Milhaud & Pierre-Emmanuel Thérond, 2016. "Tree-based censored regression with applications in insurance," Post-Print hal-01364437, HAL.
    17. Weining Shen & Jing Ning & Ying Yuan & Anna S. Lok & Ziding Feng, 2018. "Model†free scoring system for risk prediction with application to hepatocellular carcinoma study," Biometrics, The International Biometric Society, vol. 74(1), pages 239-248, March.
    18. Aasthaa Bansal & Patrick J. Heagerty, 2018. "A Tutorial on Evaluating the Time-Varying Discrimination Accuracy of Survival Models Used in Dynamic Decision Making," Medical Decision Making, , vol. 38(8), pages 904-916, November.
    19. Ruosha Li & Jing Ning & Ziding Feng, 2022. "Estimation and inference of predictive discrimination for survival outcome risk prediction models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(2), pages 219-240, April.
    20. Susana Díaz-Coto & Pablo Martínez-Camblor & Sonia Pérez-Fernández, 2020. "smoothROCtime: an R package for time-dependent ROC curve estimation," Computational Statistics, Springer, vol. 35(3), pages 1231-1251, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jcjust:v:80:y:2022:i:c:s0047235220302749. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jcrimjus .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.