Dear friends. I have the problem of assessing the importance of bleeding times censored at 20 minutes for predicting blood loss incurred after a liver biopsy. How would I use the knowledge that the censored values were 20 minutes or more ? Best wishes Troels Troels Ring, MD Department of Nephrology Aalborg Hospital, Denmark tring at mail1.stofanet.dk -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
truncated regressor
2 messages · Troels Ring, Brian Ripley
On Sun, 14 May 2000, Troels Ring wrote:
Dear friends. I have the problem of assessing the importance of bleeding times censored at 20 minutes for predicting blood loss incurred after a liver biopsy. How would I use the knowledge that the censored values were 20 minutes or more ?
This is a (partially) missing-value problem. Are values > 20 mins always censored? If so I would group the times and use an ordered factor as a regressor. If you really want a linear effect on, say `bt' you can use ... + bt + I(bt==20) + ... which allows a separate value of bt==20 over and above a linear model. If your times are not all censored, you could build a model for the missing data and use multiple imputation. If you need, that, more details of your problem, please.
Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272860 (secr) Oxford OX1 3TG, UK Fax: +44 1865 272595 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._