Timeline for In data setup for Cox regression, how to handle a subject's time before treatment of interest (i.e. before time-zero)?
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
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| Mar 21, 2022 at 17:05 | vote | accept | logjammin | ||
| Mar 21, 2022 at 4:50 | comment | added | Todd D | What you describe is the right approach, but whether the covariates allow you to accurately measure the treatment effect is a matter of content/disease knowledge. | |
| Mar 21, 2022 at 4:48 | comment | added | logjammin |
Right. So if the right covariates are included in the Cox model, would that be enough to make the treated and un-treated as similar as possible in the HR for treatment? Using the language of my table, if the right side of the model looked like = b(treatment) + b(covariate_1) + b(covariate_2) ?
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| Mar 21, 2022 at 4:33 | comment | added | Todd D | Yes, the two groups should be as similar to one another as is possible except for their treatment status. This likeness between groups is what gives a randomized trial its ability to discern the true effect of treatment. All other designs are affected by bias, which obscures the measurement of a treatment’s true effect. | |
| Mar 21, 2022 at 4:23 | comment | added | logjammin | This aligns with where my intuition has been shifting. Thanks. Tell me, though: does it matter that time-zero is different for the treated and the not-treated? In this (observational and retrospective) study's case, the time at-risk for the treated would be "time of treatment until time outcome or censoring", while for the not-treated, it would be "time of appearance in the data until outcome or censoring". Does each group's time at-risk need to be strictly comparable? | |
| Mar 21, 2022 at 4:08 | history | answered | Todd D | CC BY-SA 4.0 |