Consider a pair of regression models based on the same covar…

Consider a pair of regression models based on the same covariates with Model A: Surv(Time, Status) ~ Sex + Age + Genotype + Rx Model B: Surv(Time, Status) ~ Sex + Age + Genotype*Rx Considering ONLY the main effects coefficient for each of the covariates below, which estimates will have different interpretations in the two models? Ignore any potential numerical changes in the estimates themselves and focus on the actual meaning of the coefficients. Sex: [q1] Age: [q2] Genotype: [q3] Rx: [q4]

In the scenarios below, the log-rank test would have the low…

In the scenarios below, the log-rank test would have the lowest statistical power for [q1]. A weighted log-rank test would have the greatest increase in power over the unweighted log-rank test for [q2], and an unweighted log-rank test would have the highest power relative to a weighted test in [q3].