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Supplying user-created weights to adjustedcif with method=iptw? #20
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Thanks for the kind words. In the current version I rely on the However, you can use Hope this helps! |
I appreciate the fast and helpful reply, that makes sense! In prior work I have bootstrapped to get 95% CIs for parameters from a IPT-weighted Aalen-Johansen estimator to get around the "no nice formula for its variance" issue. But I was excited when I saw that the adjustedcif function could provide the CIs without bootstrapping (I am using multiple imputation and combining it with bootstrapping is computationally intensive). The weights from method=iptw would potentially even be the same as my user-defined weights, I just wanted a way to report balance metrics. Just an idea--I'm sure it would be quite a bit of work--but an option to output SMD values would be awesome (and average SMDs if using a multiple impution mids object). Think this would involve integration with the cobalt package. Cheers again on the great contribution! |
No problem! And thank you for the suggestion. I thought about implementing stuff like balance metrics etc. when I first built this package and ultimately decided against it for the following reasons: 1.) Large packages are hard to maintain. This package is very large already (and is going to get larger with each method that I can find and implement). So I try to focus on the most important part, which is estimation methods + visualization tools. That being said, maybe it would be a good idea to write some functions for the Might be a while till I get to it, but I will keep this issue open for now. If you want to participate directly you are of course highly welcome to do so. |
Thank you for your terrific work with this package; it is incredibly helpful and thorough! Was delighted when I found this package.
My question pertains to the adjustedcif function when one is using method=iptw. Is there any way to pass a vector of weights instead of a model to the treatment_model argument? This would be similar to the functionality offered by method=iptw for the adjustedsurv function. Asking because it would be great to estimate weights outside of the package and then just supply the user-created weights to the treatment_model argument of adjustedcif.
Reasons for wanting to externally generate weights: ability to try different packages for weight creation (WeightIt versus PSWeight), trim weights, assess covariate balance, etc.
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