Comments (2)
Nothing to do with the hazard.
The outcome model is the fit of the expectation E[Y|\bar{L},\bar{A}] (over many time-points).
If the observed \bar{A} is not consistent with following the rule (dynamic or static), the above regression will be only fit among the observations who are actually following the rule.
Claro?
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So is this most applicable for a target parameter like a data-adaptive parameter? When you intervene on treatment according to a rule, isn't everyone following that rule at each time point under the intervened treatment? Under what circumstance would you calculated a treatment-specific mean but only over individuals who actually followed that treatment?
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Related Issues (20)
- add option for isotonic regression on cumulative risks estimates over time
- Add option for observation weights HOT 2
- Return a warning when g^*=NA
- IPW for Categorical Exposure with 4 levels HOT 1
- Defining counterfactual dynamic treatment nodes with multiple dummy exposure HOT 4
- Better docs of the function output
- option : return_wts = TRUE dose not work for survNPMSM and only return results when used in directIPW HOT 5
- sequential randomization HOT 3
- using stremr without monitoring HOT 7
- stremr output HOT 1
- Fit treatment propensity based only on initial time point HOT 8
- package dependencies
- Problem with CVTMLE
- Time dependent propensity models HOT 3
- ID cannot be a factor, all character variables will be ignored
- inconsistency between doc and implementation for getIPWeights
- getIPWeights - need to add a check that user has specified PS model for all nodes on which we intervene
- bug in defineMONITORvars
- older version of stremr and new version of sl3 are not compatible
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