TESTING COVARIATE EFFECTS IN AALENS LINEAR HAZARD MODEL

The performance of tests in Aalen's linear regression model is studied using asymptotic power calculations and stochastic simulation. Aalen' s original least squares test is compared to two modifications: a weig hted least squares test with correct weights and a test where the vari ance is re-estimated under the null hypothesis. The test with re-estim ated variance provides the highest power of the tests for the setting of this paper, and the gain is substantial for covariates following a skewed distribution like the exponential. It is further shown that Aal en's choice for weight function with re-estimated variance is optimal in the one-parameter case against proportional alternatives.