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Instructions for analyzing survivor functions and fitting various distributions to failure times and survival data from experiments and patient studies. Topics include maximum likelihood estimation, confidence intervals, likelihood ratio tests, bic and aic procedures, and kaplan-meier estimates. The data sets involve high-speed turbine engines, melanoma patients, polyethylene cable insulation, electrical appliances, and breast cancer patients.
Typology: Exercises
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(a) Assuming that the failure time in each sample came from a Weibull distri- bution, obtain the maximum likelihood estimates of parameters and find 95% confidence interval for the tenth percentile of each distribution.
(b) Give the plot of five survivor functions on the same axes. carry out a comparison of the five survivor functions. Test the equality of five survivor functions.
(c) Investigate whether a log-normal distribution also fits the data by considering a generalized gamma model. Compare confidence interval for tenth percentile under a log-normal model with those in part (a)
(a) Make a probability plot for each of the following distributions: exponential, Weibull, lognormal, and log-logistic distribution. Which distribution provides a reasonable fit to the data? Estimate the parameter of the distribution chosen.
(b) Make the Cox-Snell residual plot for each of the following distributions: ex- ponential, Weibull, lognormal, log-logistic, and generalized gamma distribution. Which distribution provides a reasonable fit to the data?
(c) Obtain the log-likelihoods for exponential, Weibull, lognormal, and general- ized gamma distribution. Perform the likelihood ratio test and select the best distribution among these four distributions.
(d) Use BIC and AIC procedure to select the best distribution among the four distributions in part (c) plus the log-logistic distribution.
(e) Compare the results obtained in parts (a) − (d). In addition, compare the maximum likelihood estimates of the parameters with those obtained by graphical methods.
(a) Compare two survivor functions by likelihood ratio test.
(b) Assess the possible superiority of Type II insulation.
(a) Give the Kaplan-Meier estimate and plot of survivor function.
(b) The data suggest that the hazard function might have two components, one consisting of a fairly small portion of the distribution and giving small failure times, and one giving a wide range of larger failure time. Therefore, we might consider the following mixture model
f (t) = pf 1 (t) + (1 − p)f 2 (t)
and consequently S(t) = pS 1 (t) + (1 − p)S 2 (t)
Consider a mixture of two Weibull componets, with S 1 (t) and S 2 (t) are given by Sj (t) = exp [−(λj t)γj^ ] j = 1, 2 (i) Find the maximum likelihood equations.
(ii) The maximum likelihood estimates of parameters are
ˆp = 0. 137 , ˆλ 1 = 0. 01048 , ˆγ 1 = 1. 66 , ˆλ 2 = 0. 00036 , γˆ 1 = 1. 40.
Find the Cox-Snell residual plot for the mixture model. Does the Weibull mixture agree with observed data?