Study On The Model With Censored Data

In this article we study the semiparametic proportional odds model with random effects for correlated, specified-censored failure time data,specificallywhere X_ij is d₁-vector of covariate, β is a set of unknow regression parameters, b_i is a set of unobserved random effect and follows a normal distribution with zero mean and covariance matrix I. is the survial function conditional on X_ij and b_i.First, we obtain some regulary conditons, which ensure that our model is feasible. Then our inference imply that the maximization can be realized via Newton-Raphson algorithms.Second, the article shows that our estimation is consistent and asymptotically normal and shows the limiting variance.At last, the merits and weaknesses of the model are discussed.