Dear All Does any one know if the following survival analysis exists, and if so, is it available in R?
I am trying to parametrically model survival where some events happen at time = 0. I am particularly interested in generating the 95% confidence interval around the survival function over its full range (including time=0). For example, the data below are for time (Time) to component failure (Status =1) for a set of 10 new components. Failure is recorded in 9 components, the first 3 of which failed to start (Status=1, Time=0). > Time [1] 0 0 0 8 16 17 17 22 23 28 > Status [1] 1 1 1 1 1 1 1 1 1 0 I know how to do this in two parts (using a parametric survival model where Time>0 to develop confidence intervals over the range Time>0, and using the proportion of failures to start to generate a binomial confidence interval for Time=0). But I am hoping there is a single modelling approach - in this case it would suggest likelihood of survival at Time=0 is <1, rather than the models I am familiar with that indicate survival probabilityat Time=0 is always 1. Any suggestion would be appreciated Dr Terry Beutel Senior Scientist Agri-Science Queensland ********************************DISCLAIMER**************...{{dropped:15}} ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.