search for: steyerberg

...c package does this only for binary outcome, while rcorrp.cens() does take survival object, but doesn't output NRI or IDI. Can anyone suggest any other packages that can calculate NRI and IDI for survival data? The reference for NRI extending to survival data is: Pencina MJ, D'Agostino RB, Steyerberg EW (2011): Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat in Med 30:11-21 Thanks! John [[alternative HTML version deleted]]

Dear R fans, I am trying to do step-wise linear regression using the F-test to decide which variables to admit. Ewout Steyerberg suggests using the F-test for this purpose. I first build a model using no variables using lm(y ~ 1) and then using one variable that is a strong predictor using lm(y ~ x). When I call var.test on these two models, I do not get a significant p-value—0.07. But a summary of the second model gives...

Hi, this is not R technical question per se. I know there are many excellent statisticians in this list, so here my questions: I have dataset with ~1800 observations and 50 independent variables, so there are about 35 samples per variable. Is it wise to build a stable multiple logistic model with 50 independent variables? Any problem with this approach? Thanks John

...ot clear to me how to interpret the two different curves that are generated (logistic vs. nonparametric). The documentation doesn't enter into any detail on this point, and to a non-statistician like myself it isn't obvious. If I compare the output to that of the val.prob.ci function by E. Steyerberg, it looks like the non-parametric curve is a smoothed line between the means of quantiles. But what is then the logistic calibration line? Most grateful for any help to understand this. Best, Gustav Gustav Nilsonne, MD, PhD Postdoc +46 (0) 736-798 743 Stockholm University Stress Research Insti...

..._perf+sero_WBC, data=data1, x=TRUE, y=TRUE) fit validate(fit, method="boot", B=40,bw=TRUE, rule="p", type="residual", sls=0.15, aics=0, pr=TRUE) Due to my small data set 153 patients with 130 events I have chosen to lift the p limit from 5% to 15% as suggested by Steyerberg. ************************************************************************ I would appreciate any help with the lock term (also if it cannot be done) As I mentioned I am a bit of a rookie, and not too experienced as a programmer (I am a MD after all) However I am quite impressed with R so fa...

Ein eingebundener Text mit undefiniertem Zeichensatz wurde abgetrennt. Name: nicht verf?gbar URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20120604/b313c7fa/attachment.pl>

Dear All, Suppose that you are trying to create a binary logistic model by trying different combinations of predictors. Has R got an automatic way of doing this, i.e., is there some way of automatically generating different tentative models and checking their corresponding AIC value? If so, could you please direct me to an example? Thanks in advance, Paul

Greetings, I have generated several ROC curves and would like to compare the AUCs. The data are cross sectional and the outcomes are binary. I am testing which of several models provide the best discrimination. Would it be most appropriate to report AUC with 95% CI's? I have been looking in to the "net reclassification improvement" (see below for reference) but thus far I can only

Fixed 'maxiter' in the help file. Thanks. Please give the original source of that dataset. That dataset is a tiny sample of GUSTO-I and not large enough to fit this model very reliably. A nomogram using the full dataset (not publicly available to my knowledge) is already available in http://biostat.mc.vanderbilt.edu/tmp/bbr.pdf Use lrm, not lrm.fit for this. Adding maxit=20 will