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Turnover modeling and event history analysis

Published online by Cambridge University Press:  13 November 2019

Rodney A. McCloy*
Affiliation:
Human Resources Research Organization
Justin D. Purl
Affiliation:
Human Resources Research Organization
Erin S. Banjanovic
Affiliation:
Human Resources Research Organization
*
*Corresponding author. Email: [email protected]

Abstract

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Type
Commentaries
Copyright
© Society for Industrial and Organizational Psychology 2019 

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Footnotes

The current affiliation for author Justin D. Purl is Google.

References

Allison, P. D. (1984). Event history analysis: Regression for longitudinal event data (Sage University paper series on quantitative applications in the social sciences, Number 07-046). Beverly Hills, CA: Sage.CrossRefGoogle Scholar
Cox, D. R. (1972). Regression models and life tables. Journal of the Royal Statistical Society, 34, 187202.Google Scholar
Diaz, T. E., Sticha, P. J., Mackin, P., Hogan, P., Rinde, S., & Jose, I. (2014). Decision support tool prototype for the Enlistment Incentive Review Board: Phase 2 (interim report). Fort Belvoir, VA: U.S. Army Research Institute for the Behavioral and Social Sciences.Google Scholar
Guo, G. (1993). Event-history analysis for left-truncated data. Sociological Methodology, 23, 217243.CrossRefGoogle ScholarPubMed
Hom, P. W., Mitchell, T. R., Lee, T. W., & Griffeth, R. W. (2012). Reviewing employee turnover: Focusing on proximal withdrawal states and an expanded criterion. Psychological Bulletin, 138(5), 831858.CrossRefGoogle ScholarPubMed
Kalbfleisch, J. D., & Prentice, R. L. (1980). The statistical analysis of failure time data. New York, NY: John Wiley and Sons.Google Scholar
Lancaster, T. (1990). The econometric analysis of transition data. New York, NY: Cambridge University Press.Google Scholar
Lawless, J. F. (1982). Statistical models and methods for lifetime data. New York, NY: John Wiley & Sons.Google Scholar
Lee, T. W., & Mitchell, T. R. (1994). An alternative approach: The unfolding model of voluntary employee turnover. Academy of Management Review, 19, 5189.CrossRefGoogle Scholar
Mobley, W. H. (1977). Intermediate linkages in the relationship between job satisfaction and employee turnover. Journal of Applied Psychology, 62(2), 237240.CrossRefGoogle Scholar
Singer, J. D., & Willett, J. B. (1991). Modeling the days of our lives: Using survival analysis when designing and analyzing longitudinal studies of duration and the timing of events. Psychological Bulletin, 110(2), 268290.CrossRefGoogle Scholar
Singer, J. D., & Willett, J. B. (1993). It’s about time: Using discrete-time survival analysis to study duration and the timing of events. Journal of Educational Statistics, 18(2), 155195. doi:10.3102/10769986018002155Google Scholar
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis. New York, NY: Oxford University Press.CrossRefGoogle Scholar
Speer, A. B., Dutta, S., Chen, M., & Trussell, G. (2019). Here to stay or go? Connecting turnover research to applied attrition modeling. Industrial and Organizational Psychology: Perspectives on Science and Practice, 12(3), 272–296.Google Scholar