Thank you David. This was very insightful. You've helped me understand
that maternal penicillin allergy is unlikely to influence the risk of
neonatal sepsis, *except* through the choice of intra-partum antibiotic
given to the mother. So no confounding with allergy; it's just the
reason why a mother might be given a non-penicillin antibiotic in labor.
Thanks.
--Chris Ryan
David Miller via American Statistical Association wrote:
> You're asking a good question, and, to answer it, it's helpful to
> understand the purpose of propensity scores in this context. Propensity
> scores...
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> Re: propensity score methods when some subjects have a 0 probability of
> receiving one of the treatments
> <https: community.amstat.org cnsl discussion propensity-score-methods-when-some-subjects-have-a-0-probability-of-receiving-one-of-the-treatments#bm704146a3-54a3-468a-81da-aea932301a1f>
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> David Miller
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> Aug 24, 2026 3:22 PM
> David Miller
> <https: community.amstat.org profile?userkey=128795b8-780f-4871-acf1-45bb4b8b7016>
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>
> You're asking a good question, and, to answer it, it's helpful to
> understand the purpose of propensity scores in this context. Propensity
> scores are intended to account for potential confounding by mimicking a
> randomized experiment. Confounding occurs if and only if a variable is
> associated with both the outcome and the treatment assignment. In a
> randomized experiment, treatments are assigned at random to remove
> confounding. Propensity scores attempt to estimate the probability of
> treatment assignments such that each treatment is assigned at random
> with a specific probability conditional on the propensity score. We're
> kind of pretending that every patient was randomized, but all with
> different probabilities for each treatment.
>
> With that context in mind, you can't address confounding with propensity
> scores if the probability of a treatment assignment is zero. Keep in
> mind though that two things have to be true for confounding to occur.
> The confounder has to be associated with the treatment assignment and
> the confounder has to be associated with the outcome. If there is
> substantial biological and/or experimental data to suggest that allergy
> is unrelated to the outcome, you could consider leaving allergy out of
> your propensity score and admit that you can't rule it out as a
> confounding factor. The alternative is to exclude those patients from
> your analysis. In other words, either ignore allergy completely (while
> admitting you are doing so), or use it as an exclusion. Don't attempt to
> make an adjustment for it that isn't possible.
>
> My two cents (reasonable practitioners may differ for good reasons, and
> reviewers at an average medical journal are even more likely to differ
> for poor reasons)
>
>
>
> ------------------------------
> David Miller
> Principal
> DPM Biostatistics LLC
> ------------------------------
>
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> -------------------------------------------
> Original Message:
> Sent: 08-23-2026 23:33
> From: Christopher Ryan
> Subject: propensity score methods when some subjects have a 0
> probability of receiving one of the treatments
>
> 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."
>
> pmc.ncbi.nlm.nih.gov/articles/PMC3144483/#R13
> <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
> ------------------------------
>
>
>
>
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Original Message:
Sent: 8/24/2026 3:22:00 PM
From: David Miller
Subject: RE: propensity score methods when some subjects have a 0 probability of receiving one of the treatments
You're asking a good question, and, to answer it, it's helpful to understand the purpose of propensity scores in this context. Propensity scores are intended to account for potential confounding by mimicking a randomized experiment. Confounding occurs if and only if a variable is associated with both the outcome and the treatment assignment. In a randomized experiment, treatments are assigned at random to remove confounding. Propensity scores attempt to estimate the probability of treatment assignments such that each treatment is assigned at random with a specific probability conditional on the propensity score. We're kind of pretending that every patient was randomized, but all with different probabilities for each treatment.
With that context in mind, you can't address confounding with propensity scores if the probability of a treatment assignment is zero. Keep in mind though that two things have to be true for confounding to occur. The confounder has to be associated with the treatment assignment and the confounder has to be associated with the outcome. If there is substantial biological and/or experimental data to suggest that allergy is unrelated to the outcome, you could consider leaving allergy out of your propensity score and admit that you can't rule it out as a confounding factor. The alternative is to exclude those patients from your analysis. In other words, either ignore allergy completely (while admitting you are doing so), or use it as an exclusion. Don't attempt to make an adjustment for it that isn't possible.
My two cents (reasonable practitioners may differ for good reasons, and reviewers at an average medical journal are even more likely to differ for poor reasons)
------------------------------
David Miller
Principal
DPM Biostatistics LLC
------------------------------