Peter Dalgaard-2 wrote > >> I fit a coxph model: >> >> coxphfit <- coxph(Surv(sampledLifetime, !sampledCensoredQ) ~ curpbc6 + >> prevpbc6, sampledTimeSeries) >> >> Now I'm trying to predict the expected number of events using a new >> dataset. >> The documentation suggests that >> >> coxPred <- predict(coxphfit, newdata = testTimeSeries, type="expected") >> >> will do what I want, but I get the error >> >> Error in model.frame.default(data = testTimeSeries, formula = >> Surv(sampledLifetime, : >> variable lengths differ (found for 'curpbc6') >> >> when I do this. The dataframes sampledTimeSeries and testTimeSeries were >> constructed by taking rows from a larger dataframe, so they have the same >> data. >> >> What am I doing incorrectly? > > Most likely referring to a variable not in testTimeSeries. (I kind of > suspect that unlike predict.lm, predict.coxph does not ignore the left > hand side of formulas. Does testTimeSeries contain a sampledLifetime > column?) >
No, I did not have the lifetime and censored data in the dataframe. Per your idea, I put the sampledLifetime and and sampledCensoredQ variables in the dataframe sampledTimeSeries and left the rest of the code the same. Now when I try with the new data set, coxPred <- predict(coxphfit, newdata = testTimeSeries, type="expected") I get different errors. If I use testTimeSeries without the lifetime and censor indicator columns (which shouldn't be required for prediction), then i get the same error as before. If I put in these columns, then I get the error Error in predict.coxph(coxphfit, newdata = testTimeSeries, type = "expected", : object 'x' not found -- View this message in context: http://r.789695.n4.nabble.com/predicting-expected-number-of-events-using-a-coxph-model-tp4634935p4635168.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
