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...o by bootstrap covariance matrix and Huber-White sandwich method, respectively. > MyModel.boot <- bootcov(MyModel, B=1000, coef.reps=T) > MyModel.robcov <- robcov(MyModel) > anova(MyModel) Wald Statistics Response: outcome Factor Chi-Square d.f. P stenosis 0.20 1 0.6547 x1 10.69 1 0.0011 x2 2.33 1 0.1270 procedure 3.27 1 0.0708 ClinicalScore 2.55 1 0.1102 TOTAL 18.71 5 0.0022 > anova(MyModel.boot) Wald Statistics Response: out...

...the full model by step-down technique predicting L from all of the componet variables using ordinary least squares (ols in rms package) as the followings. I would like to know whether I am doing right or not. > library(rms) > plogit <- predict(full.model) > full.ols <- ols(plogit ~ stenosis+x1+x2+ClinicalScore+procedure, sigma=1) > fastbw(full.ols, aics=1e10) Deleted Chi-Sq d.f. P Residual d.f. P AIC R2 stenosis 1.41 1 0.2354 1.41 1 0.2354 -0.59 0.991 x2 16.78 1 0.0000 18.19 2 0.0001 14.19 0.882 procedure 26.12 1...

...bootcov) was narrower than CIs provided by usual variance-covariance matrix in the followings. My data has no cluster structure. I am wondering which confidence interval is better. I guess bootstrapping one, but is it right? I would appreciate anybody's help in advance. > summary(MyModel, stenosis=c(70, 80), x1=c(1.5, 2.0), x2=c(1.5, 2.0)) Effects Response : outcome Factor Low High Diff. Effect S.E. Lower 0.95 Upper 0.95 stenosis 70.0 80 10.0 -0.11 0.24 -0.59 0.37 Odds Ratio 70.0 80 10.0 0.90 NA 0.56 1.45...

Dear colleagues, I hope someone can help me with my problem. I have fitted a cox model with the following syntax: # cox01def <-cph(Surv(TEVENT,EVENT) ~ ifelse(AGE>50, (AGE-50)^2,0) + BMI + # HDL+DIABETES +HISTCAR2 + log(CREAT)+ as.factor(ALBUMIN)+STENOSIS+IMT,data # = XC, x=T, y=T, surv=T) *1 Furthermore I have estimated my beta's also with a Lasso method - Coxpath ( from Glmpath pckage) , namely: # LASSOdata <- list(x=cox01$x, time=XC$TEVENT, status=XC$EVENT) # summary(LASSOdata) # LASSOpath <- coxpath(data=SMARTdata) My problem is...

...[0x547cbe] Thread 5e52b7c Kernel stack: 14 IOWorkLoop::threadMain() + 0 [0x547cbe] ************************************************ Emil Olsen DVM, Ph.D Student KU LIFE DK & RVC UK Supported by Faxe Animal Hospital Working title: "Diagnosing Equine Cervical Vertebral Stenosis" Frederiksberg DK & Hatfield UK +45 20921986 / +44 7503 287711 eo at life.ku.dk

...ext/plain; charset="us-ascii" Dear colleagues, I hope someone can help me with my problem. I have fitted a cox model with the following syntax: # cox01def <-cph(Surv(TEVENT,EVENT) ~ ifelse(AGE>50, (AGE-50)^2,0) + BMI + # HDL+DIABETES +HISTCAR2 + log(CREAT)+ as.factor(ALBUMIN)+STENOSIS+IMT,data # = XC, x=T, y=T, surv=T) *1 Furthermore I have estimated my beta's also with a Lasso method - Coxpath ( from Glmpath pckage) , namely: # LASSOdata <- list(x=cox01$x, time=XC$TEVENT, status=XC$EVENT) # summary(LASSOdata) # LASSOpath <- coxpath(data=SMARTdata) My problem is...