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...where n is the sample size and _pi = 3.141592654 ... 4. In case of ties in the original xb, substitute average zi's over each of the tied sets. 5. Perform regression (e.g. Cox) on z = z1,...,zn. I can obviously do steps 1 and 2: # step 1 # cox1 <- cph(Surv(stime1,eind1)~adat1+bdat1+c11+c21) c1dat <- cox1$linear.predictors # step 2 # ris <- rank(c1dat,ties.method="minimum") Can anyone advise how I might invoke the inverse normal. I thought 'qnorm' may be an option but I'm lacking the necessary parameters within the framework above. Many thanks, Laura [[alter...