Plot 95% Confidence Interval R
Plot 95% Confidence Interval R Average ratng: 4,6/5 6601 votes
Construct A 95 % Confidence Interval
>
> Figure 3 is
> http://i3.6.cn/cvbnm/a9/c8/8b/c01aad248a0b4ae6ef677600614bd4fa.jpg
>
>
> 2009/7/26 Frank E Harrell Jr <[hidden email]
> <mailto:[hidden email]>>
> >
> > zhu yao wrote:
> >>
> >> Dear experts:
> >>
> >> I am a newbie to R. Recently, I try to make prediction models with R
> and the
> >> Design library.
> >> I have read Prof. Harrell's excellent book. But I did not quite
> understand.
> >> I have two problems about the validation and calibration of prediction
> >> models:
> >> 1. Can someone explain the results outputted by the validate()
> function? How
> >> to get 95% of c-value of validate?
> >
> > validate does not provide that confidence interval, unfortunately.
> >
> >> 2. How to add 95% ci in the calibration plot?
> >
> > That is not provided except for survival models.
> >
> > Next time please include your code so we can see what model you are
> using.
> >
> > Thanks
> > Frank
> >
> >>
> >> Yao Zhu
> >> Department of Urology
> >> Fudan University Shanghai Cancer Center
> >>
> >> [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> [hidden email] <mailto:[hidden email]> 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.
> >>
> >
95% Confidence Interval R Code
Scatter Plot With 95 Confidence Interval R
The R package boot allows a user to easily generate bootstrap samples of virtually any statistic that they can calculate in R. From these samples, you can generate estimates of bias, bootstrap confidence intervals, or plots of your bootstrap replicates. How to add 95% confidence intervals in the calibration plot? Dear experts: I am a newbie to R. Recently, I try to make prediction models with R and the Design library. I have read Prof. By default, the confidence interval is calculated based on the alpha/2-quantile of the t-distribution, where alpha = 0.05. This is motivated if the data are normally distributed. It can be changed to the alpha/2-quantile of the normal distribution.