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...k=2, data = rotterdam) # obtain the linear predictor for each patient predf <- model.matrix(fit1) %*% fit1$res[-(1:4),"est"] # Predict baseline survival at 5 years y5_Flex_1 <- summary(fit1,type="survival",t=5) y5_Flex <- y5_Flex_1[[1]]$est y5_Flex # Shrinkage factor vanH <- 0.9589255 heuristic_lp_flex = vanH*predf?????? # Now calculate the shrunken model baseline survival prob at 5 years by fixing the shrunken lp as an offset and predicting the baseline survival fit1_shrunk <- flexsurvspline(Surv(rfstime,rfs)~offset(heuristic_lp_flex),k=2,data=rotterdam) Th...