I am trying to simulate the survival data (by using Weibull distribution) that can fit the Cox model below:
h(t) = ho(t). exp(beta1 * X1 + beta2 * X1 * X2)
X1 and X2 are binary.
I haved tried using the linear predictor lp = exp(beta1*X1 + beta2 * X1 * X2) but it seems wrong. When I fitted the Cox model later on, the estimated beta1 and beta2 are absolutely different with the value of beta1 and beta2 that I have used to simulate data.
Someone can help me please? Thankyou so much.