Timeline for Schoenfeld residuals - Plain English explanation, please!
Current License: CC BY-SA 4.0
10 events
| when toggle format | what | by | license | comment | |
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| Jun 12 at 15:56 | comment | added | EdM | @DeviSita you can think of the risk set for an event time as being all those still under observation immediately prior to that event time. Thus it includes both those who have the event at that time and those who don't. In your example, that's all 7 individuals. | |
| Jun 12 at 11:44 | comment | added | Devi Sita | RS = risk scores | |
| Jun 12 at 11:42 | comment | added | Devi Sita | Hi @EdM you wrote this "You start by determining, for each event time, the risk-weighted averages of covariate values and the corresponding risk-weighted covariance among covariate values over all individuals at risk at that time". When calculating the risk-weighted averages for time 10 fx and let us assume two got the event at time 10, and five did not. Does this mean that the total risk are the sum of the RS for the five individuals who did not get the event at time 10? or is it the total risk = five+two=7? I want to understand who is part of the "over all individuals at risk at that time" | |
| Jan 4 at 22:29 | history | edited | EdM | CC BY-SA 4.0 |
Clarified implementation of scaling
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| Jun 1, 2022 at 16:19 | history | edited | EdM | CC BY-SA 4.0 |
clarified potentially misleading sentence
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| Oct 8, 2021 at 18:09 | comment | added | EdM | @user333336 I'm not sure that I completely "got it" until I tried to answer this question. For most purposes, the "simple answer" should suffice, the rest just says why it's true. | |
| Oct 8, 2021 at 17:48 | comment | added | user333336 | thank you so much for such a thorough explanation. Although some of the answer went over my head, it gives me something to get my teeth into! :) | |
| Oct 5, 2021 at 16:38 | history | edited | EdM | CC BY-SA 4.0 |
added 39 characters in body
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| Oct 5, 2021 at 16:30 | history | edited | EdM | CC BY-SA 4.0 |
added reference link
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| Oct 5, 2021 at 16:21 | history | answered | EdM | CC BY-SA 4.0 |