Hanjoe Kim posted on Wednesday, January 20, 2016 - 6:33 pm
I am trying to understand the HAZARDC command. First I thought that this command is used to specify the censoring proportion in data but I learned that the value given here is the lambda value for an exponential parameter. From Asparouhov and Muthen (2014), if lambda=lambda1 (where lambda is defined within Model Population T#1*lambda with GENERATE = T(s) and lambda1 is the value used in HAZARDC), about 50% of the observations will be censored.
Can you give me guidance to adjust the censoring proportion in Monte Carlo generated data? For example, if T#1*.1, then HAZARDC=T(.1) will give about 50% censoring. Given that the lambda value is fixed at .1, what would the lambda1 values be to get 10% or 30% censoring?
We generate the survival variable T and independently censoring variable C with exponential distribution with parameter given by the HAZARDC command. If C > T the variable is not censored. If C < T the T variable is censored at time C.