Statistical identification of employees with unusual sick leave usage patterns can result in false
positive identifications. Such misidentifications weaken confidence in detection methods and
may increase reluctance of supervisors to pursue reported unusual sick leave use. A computer
simulation model was used to evaluate alternate methods and parameters of unusual sick leave
detection. Results of the simulation were used to refine identification parameters and to modify
supervisory follow-up procedures.
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References
1.
Avery, R.B., and V.J. Hotz.1984. Statistical models for analyzing absentee behavior. In Absenteeism, edited by P. S. Goodman and R. S. Atkin.San Francisco: Jossey-Bass.
2.
Farrell, D., and C.L. Stamm.1988. Meta-analysis of the correlates of employee absence. Human Relations41(3): 211-27.
3.
Gardiner, R.C.1992. Tracking and controlling absenteeism. Public Productivity and Management Review25(3): 289-307.
4.
Hulin, C.L.1984. Suggested directions for defining, measuring and controlling absenteeism. In Absenteeism, edited by P. S. Goodman and R. S. Atkin.San Francisco: Jossey-Bass.
5.
Keim, J.A., and D.L. Quigg.1987. The sickout: Using and evaluating statistical evidence in a prima facie case. Employee Relations Law Journal13(3): 445-64.
6.
Landy, F.J., J.J. Vasey, and F.D. Smith.1984. Methodological problems and strategies in predicting absence. In Absenteeism, edited by P. S. Goodman and R. S. Atkin.San Francisco: Jossey-Bass.
7.
Naylor, T.H., J.L. Balintfy, D.S. Burdick, and K. Chu.1966. Computer simulation techniques. New York: Wiley.
8.
Steers, R.M., and S.R. Rhodes.1978. Major influences on employee attendance: A process model. Journal of Applied Psychology63(4): 391-407.
