I may be making my first foray into propensity score methods. Probably in over my head--but I suppose that's a good way to learn.
The context is a planned observational study based on existing electronic medical record data. There are multiple treatments, each one a different antibiotic for laboring mothers known to be colonized by S. agalactiae, otherwise known as "group B strep". The outcome is binary: occurence of S. agalactiae sepsis in the newborn.
I find in a number of sources the caution/admonition/requirement that every subject must have a non-zero probability of receiving each of the treatments. For example, this excerpt from Austin et al (in turn from Rosenbaum and Rubin) in the case of a binary outcome:
"Rosenbaum and Rubin (1983a) defined treatment assignment to be strongly ignorable if the following two conditions hold: (a) (Y (1), Y(0)) ╩ Z|X and (b) 0 < P(Z = 1|X) < 1. The first condition says that treatment assignment is independent of the potential outcomes conditional on the observed baseline covariates. The second condition says that every subject has a nonzero probability to receive either treatment."
https://pmc.ncbi.nlm.nih.gov/articles/PMC3144483/#R13
In my study, most laboring patients will receive pencillin or ampicillin. Some will receive a different agent, and the most likely reason for that will be a stated penicillin allergy. In practice, those patients have a 0 probability of receiving penicillin or ampicillin, absent a mishap. How much of a problem will this be? A deal-breaker? Is there a concept of "weakly ignorable?"
I would include penicillin allergy as one of the predictors in the model to produce the propensity scores.
Thanks.
------------------------------
Christopher Ryan
Agency Statistical Consulting, LLC
------------------------------