Abstract:
:Computer simulation was applied to Sartwell's model to examine the impact of competing risks of death on the underlying assumptions and the power to reject both uniform and normal incubation period distributions. Exponential and nonparametric survival functions were imposed onto lognormal, uniform, and normal distributions to create random samples reflecting competing risk. These random samples were evaluated with the Shapiro-Wilk's test to determine the proportion for which the lognormal distribution was rejected. The simulations indicated that competing causes of death do not significantly alter the lognormal distribution of incubation periods. In only approximately 5% of the samples drawn from a lognormal distribution was a lognormal hypothesis rejected with a goodness-of-fit test when sample size varied from 20 to 500. There was generally good power (> 80%) to reject a lognormal distribution if the random samples were generated from a uniform distribution of incubation times, but not when they were generated from a normal distribution, particularly with increasing ages at disease onset. Varying the standard deviation did not significantly change the simulation results if the random samples came from a lognormal or uniform distribution. These conclusions were further supported by application of Sartwell's model to published data on the ages of onset for several chronic diseases.
journal_name
Am J Epidemioljournal_title
American journal of epidemiologyauthors
Yi Q,Glickman LTdoi
10.1093/oxfordjournals.aje.a117642subject
Has Abstractpub_date
1995-08-01 00:00:00pages
363-8issue
3eissn
0002-9262issn
1476-6256journal_volume
142pub_type
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