[R] survival::survfit.coxph confidence vs prediction intervals

Dear list, I'm trying to understand what kind of uncertainty intervals are plotted for survival::survfit.coxph when 'conf.int=TRUE' is called, e.g.: f <- coxph(Surv(futime, fustat) ~ age, data = ovarian) s <- survfit(f, newdata=data.frame(age=c(30, 60))) plot(s, conf.int=TRUE) Are these bands

Re: [R] (no subject)

Hello, Can you provide more information? What is your operating system? What is your database management system (sqlite, mySQL,...) What package do you use to import the data in R from the database? What is the default language on your computer? Are the variables not in farsi fine? My guess is

[R] [R-pkgs] New package cNORM: Continuous norming

Hi everyone, I would like to introduce a new package: cNORM. It aims at solving problems with percentile estimation / norm score generation in biometrics and psychometrics, f. e. BMI growth curves, IQ tests ... Conventional methods for producing standard scores in psychometrics or biometrics

[R] D-optimum design - optimization model

Dear all, I'm trying to use the D-optimum design. In my data, the response is KIC, and 4 factors are AC, AV, T, and Temp. A typical second-degree response modeling is as follows: > data<-read.csv("2.csv", header =T) > mod <- >

[R] [R-pkgs] Introducing empirical: Probability Distributions as Models of Data

hi all I would like to introduce my R package: empirical: Probability Distributions as Models of Data The description is: Computes continuous (not step) empirical (and nonparametric) probability density, cumulative distribution and quantile functions. Supports univariate, multivariate and