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SPEAKER: |
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TITLE: |
"Alternative Time Scales in Survival Analysis" |
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DAY: |
Wednesday, March 17, 1999 |
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TIME: |
3:30 p.m. [Coffee in BSB-202 at 3:00 p.m.] |
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PLACE: |
BSB-108 |
In many reliability applications, there may not be a unique scale in which to measure time to failure or assess performance. This is especially the case when several measures of usage are available on each unit. For example, the age, the total number of flight hours, and the number of landings are often considered important in aircraft reliability. Similarly, in medical or biological applications of survival analysis, there are often alternative scales (e.g., Oakes, 1995). In this talk, we consider the definition of "good" time scale, along with methods of determining a time scale.
Thierry Duchesne obtained his B.Sc. and M.Sc. degrees in Actuarial Science from Laval University in Quebec City. He is currently completing his Ph.D. studies in Statistics at the University of Waterloo, under the supervision of Professor Jerry Lawless. His research interests include survival analysis, statistical inference, and claim amount distribution modelling.
The following references have been provided by Thierry to be used as background for his talk. The references Oakes (1995) and Kordonsky and Gertsbakh (1997) are on reserve at Thode Library (STATS 770: Statistics Seminar).
[1] Oakes, D. (1995). "Multiple Time Scales in Survival Analysis", LIFETIME DATA ANALYSIS 1, pp. 7-18.
[2] Farewell, V.T. and Cox, D.R. (1979). "A Note on Multiple Time Scales in Life Testing", APPLIED STATISTICS 28, pp. 73-75.
[3] Kordonsky, K.B. and Gertsbakh, I. (1997). "Multiple Time Scales and the Lifetime Coefficient of Variation: Engineering Applications", LIFETIME DATA ANALYSIS 2, pp. 139-156.
[4] Lin, D.Y. and Ying, Z. (1995). "Semiparametric Inference for Accelerated Life Model with Time-Dependent Covariates", JOURNAL OF STATISTICAL PLANNING AND INFERENCE 44, pp. 47-63.