Turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

- Home
- /
- Analytics
- /
- Stat Procs
- /
- the Kaplan-Meier estimator in Uno’s Concordance Statistic

Options

- RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Mute
- Printer Friendly Page

🔒 This topic is **solved** and **locked**.
Need further help from the community? Please
sign in and ask a **new** question.

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

Posted 08-23-2020 04:13 PM
(1053 views)

Based on SAS User's Guide, it uses inverse probability weighting of the Kaplan-Meier estimator of the censoring distribution at the time point just before X_i which is G(X_i-)^(-2).

However, based on Uno's paper "On the C-Statistics for Evaluating Overall Adequacy of Risk Prediction Procedures with Censored Survival Data", it used the exact time point for the Kaplan-Meier, G(X_i)^(-2). Depending on which time point I use, it would give a slightly different value of the C-index.

I am not sure why SAS used the time point just before X_i for the Kaplan-Meier estimator which is G(X_i-)^(-2) because the paper used the exact time point X_i, which is G(X_i)^(-2), for the inverse probability weighting of the Kaplan-Meier estimator.

Should I use the exact time point or the time point just before X_i?

1 ACCEPTED SOLUTION

Accepted Solutions

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

I think the most probable reason is that if you specified the exact time, the KM estimator would include any values observed up to, but not including the next time point. KM estimators are based on "open ended" intervals at the upper end, so I suspect the paper you are citing either used a 'closed end' cutoff (unlikely), or indexed the interval by the endpoint, rather than the beginning point. That is probably OK, unless you have just a single interval,

SteveDenham

5 REPLIES 5

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

Based on SAS User's Guide, it uses inverse probability weighting of the Kaplan-Meier estimator of the censoring distribution at the time point just before X_i.

However, based on Uno's paper "On the C-Statistics for Evaluating Overall Adequacy of Risk Prediction Procedures with Censored Survival Data", it used the exact time point for the Kaplan-Meier. Depending on which time point I use, it would give a slightly different value of the C-index.

Should I use the exact time point or the time point just before X_i?

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

Thank you so much for your reply!

I understood that Tau is the upper limit of the time interval.

However, the question I have is why SAS used the time point just before X_i for the Kaplan-Meier estimator which is G(X_i-)^(-2). The paper used the exact time point X_i, which is G(X_i)^(-2), for the inverse probability weighting of the Kaplan-Meier estimator.

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

I think the most probable reason is that if you specified the exact time, the KM estimator would include any values observed up to, but not including the next time point. KM estimators are based on "open ended" intervals at the upper end, so I suspect the paper you are citing either used a 'closed end' cutoff (unlikely), or indexed the interval by the endpoint, rather than the beginning point. That is probably OK, unless you have just a single interval,

SteveDenham

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

Thank you so much for your reply!

That's very helpful 😄

**SAS Innovate 2025** is scheduled for May 6-9 in Orlando, FL. Sign up to be **first to learn** about the agenda and registration!

What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.