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Survival analysisOrganizational behavior / turnover

Event History Turnover Analysis

Event history turnover analysis models not just whether employees leave but when they leave, treating tenure as a duration and the act of quitting as an event whose timing carries information. Paul Allison's 1984 monograph brought event history methods — survival and hazard models — into the social sciences with a regression-oriented treatment that handles the censoring inherent in longitudinal data. Morita, Lee, and Mowday's 1993 Academy of Management Journal paper applied these techniques to turnover research, showing organizational scholars how to model the hazard of leaving and why time-to-event methods are superior to simple stayed-versus-left comparisons. The core object is the hazard function, the instantaneous risk of quitting given that one has stayed so far, which can depend on tenure and on employee and job characteristics. Because some employees are still present when the study ends, the analysis must correctly handle censored observations rather than discarding or mis-coding them. The result is a model that explains and predicts the timing of turnover.

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Sumber

  1. Morita, J. G., Lee, T. W., & Mowday, R. T. (1993). The regression-analog to survival analysis: A selected application to turnover research. Academy of Management Journal, 36(6), 1430-1464. DOI: 10.5465/256818
  2. Allison, P. D. (1984). Event History Analysis: Regression for Longitudinal Event Data. Sage Publications (Quantitative Applications in the Social Sciences, No. 46). ISBN: 9780803920552

Cara memetik halaman ini

ScholarGate. (2026, June 23). Event History Turnover Analysis (Survival and Hazard Models of Employee Turnover). ScholarGate. https://scholargate.app/ms/organizational-behavior/event-history-turnover-analysis

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ScholarGateEvent History Turnover Analysis (Event History Turnover Analysis (Survival and Hazard Models of Employee Turnover)). Dicapai 2026-06-24 daripada https://scholargate.app/ms/organizational-behavior/event-history-turnover-analysis · Set data: https://doi.org/10.5281/zenodo.20539026