Logrank-type tests for comparing survival curves with interval-censored data
We propose logrank-type tests for comparing several survival functions from interval-censored data. The proposed tests do not require use of the so-called EM algorithm because we introduce uniform weights that depend only on the size of the risk set at each observed time instead of the weights involving estimated survivals. This technique reduces computation time. As alternatives for the estimated asymptotic variance of a proposed test statistic, we introduce estimates that mimic the logrank test and the multiple imputation method. Results from simulation studies show that our proposed tests are very satisfactory in terms of size and powers. We illustrate the proposed tests with breast cosmesis data from Finkelstein and Wolfe [1985. Biometrics 41, 933945] and lung cancer post-operative data from the Yonsei Cancer Center in Korea.
em algorithm multiple imputation lung cancer post-operative study score test