On testing dependence between time to failure and cause of failure when causes of failure are missing

The hypothesis of independence between the failure time and the cause of failure is studied by using the conditional probabilities of failure due to a specific cause given that there is no failure up to certain fixed time. In practice, there are situations when the failure times are available for al...

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Bibliographic Details
Published in:PloS one 2007-12, Vol.2 (12), p.e1255-e1255
Main Authors: Dewan, Isha, Kulathinal, Sangita
Format: Article
Language:English
Subjects:
Analysis
Biometrics
Causality
Central limit theorem
Computer simulation
Default
Economic models
Failure
Failure times
Fatalities
Hypotheses
Hypothesis testing
Inequality
Mathematics/Statistics
Models, Theoretical
Mortality
Mortgages
Motorcycles
Multivariate analysis
Normal distribution
Prepayments
Preventive maintenance
Probability
Random variables
Risk
Risk assessment
Simulation
Statistical tests
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Summary:The hypothesis of independence between the failure time and the cause of failure is studied by using the conditional probabilities of failure due to a specific cause given that there is no failure up to certain fixed time. In practice, there are situations when the failure times are available for all units but the causes of failures might be missing for some units. We propose tests based on U-statistics to test for independence of the failure time and the cause of failure in the competing risks model when all the causes of failure cannot be observed. The asymptotic distribution is normal in each case. Simulation studies look at power comparisons for the proposed tests for two families of distributions. The one-sided and the two-sided tests based on Kendall type statistic perform exceedingly well in detecting departures from independence.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0001255