Marginal structural models with monotonicity constraints: A case study in out-of-hospital cardiac arrest patients
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This paper deals with estimating the probability of a binary counterfactual outcome as a function of a continuous covariate under monotonicity constraints. We are motivated by the study of out-of-hospital cardiac arrest patients which aims to estimate the counterfactual 30-day survival probability if either all patients had received, or if none of the patients had received bystander cardiopulmonary resuscitation (CPR), as a function of the ambulance response time. It is natural to assume that the counterfactual 30-day survival probability cannot increase with increasing ambulance response time. We model the monotone relationship with a marginal structural model and B-splines. We then derive an estimating equation for the parameters of interest which however further relies on an auxiliary regression model for the observed 30-day survival probabilities. The predictions of the observed 30-day survival probabilities are used as pseudo-values for the unobserved counterfactual 30-day survival status. The methods are illustrated and contrasted with an unconstrained modeling approach in large-scale Danish registry data.
Original language | English |
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Journal | Statistics in Medicine |
Volume | 42 |
Issue number | 5 |
Pages (from-to) | 603-618 |
Number of pages | 16 |
ISSN | 0277-6715 |
DOIs | |
Publication status | Published - 2023 |
Bibliographical note
Publisher Copyright:
© 2023 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
- causal inference, g-computation, marginal structural models, penalized splines
Research areas
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