18 research outputs found

    Causal effects of intervening variables in settings with unmeasured confounding

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    We present new results on average causal effects in settings with unmeasured exposure-outcome confounding. Our results are motivated by a class of estimands, e.g., frequently of interest in medicine and public health, that are currently not targeted by standard approaches for average causal effects. We recognize these estimands as queries about the average causal effect of an intervening variable. We anchor our introduction of these estimands in an investigation of the role of chronic pain and opioid prescription patterns in the opioid epidemic, and illustrate how conventional approaches will lead unreplicable estimates with ambiguous policy implications. We argue that our altenative effects are replicable and have clear policy implications, and furthermore are non-parametrically identified by the classical frontdoor formula. As an independent contribution, we derive a new semiparametric efficient estimator of the frontdoor formula with a uniform sample boundedness guarantee. This property is unique among previously-described estimators in its class, and we demonstrate superior performance in finite-sample settings. Theoretical results are applied with data from the National Health and Nutrition Examination Survey

    Optimal regimes for algorithm-assisted human decision-making

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    We introduce optimal regimes for algorithm-assisted human decision-making. Such regimes are decision functions of measured pre-treatment variables and enjoy a "superoptimality" property whereby they are guaranteed to outperform conventional optimal regimes currently considered in the literature. A key feature of these superoptimal regimes is the use of natural treatment values as input to the decision function. Importantly, identification of the superoptimal regime and its value require exactly the same assumptions as identification of conventional optimal regimes in several common settings, including instrumental variable settings. As an illustration, we study superoptimal regimes in an example that has been presented in the optimal regimes literature

    A Graphical Description of Partial Exchangeability

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    Partial exchangeability is sufficient for the identification of some causal effects of interest. Here we review the use of common graphical tools and the sufficient component cause model in the context of partial exchangeability. We illustrate the utility of single world intervention graphs (SWIGs) in depicting partial exchangeability and provide an illustrative example of when partial exchangeability might hold in the absence of complete exchangeability

    Associations of intimate partner violence and financial adversity with familial homelessness in pregnant and postpartum women: A 7-year prospective study of the ALSPAC cohort.

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    ObjectiveTo determine whether emotional and physical intimate partner violence (IPV) and financial adversity increase risk of incident homelessness in pregnancy and the post-partum period.Study designData were drawn from the Avon Longitudinal Study of Parents and Children, which starting in 1990 mailed questionnaires to 14,735 mothers in the UK, over 7 years from pregnancy onwards. Marginal structural models and multiple imputation were used to address time-varying confounding of the primary variables, testing for interaction between concurrent emotional/physical IPV and financial adversity, and adjusted for baseline age, ethnicity, education, partner's alcohol use, parity, depression, and social class.ResultsEmotional IPV (HR 1.44 (1.13,1.84)), physical IPV (HR 2.05 (1.21,3.49)), and financial adversity (HR 1.59 (1.44,1.77)) each predicted a multiplicative increase in the discrete-time hazard of incident homelessness. We identified joint effects for concurrent emotional IPV and financial adversity (HR 2.09 (1.35,3.22)) and concurrent physical IPV and financial adversity (HR 2.79 (1.21,6.44)). We further identified a temporary decline in self-reported physical IPV among mothers during pregnancy and up to 8 months post-partum.ConclusionsEmotional and physical IPV and financial adversity independently and jointly increase the risk of incident homelessness. The effects of emotional and physical IPV are comparable to or greater than the risk of financial adversity. Homelessness prevention policies should consider IPV victims as high-risk, regardless of financial status. Furthermore, self-reported physical IPV declines temporarily during pregnancy and up to 8 months post-partum. Screening for IPV in this period may miss high-risk individuals

    Causal inference with limited resources: proportionally-representative interventions

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    Investigators often evaluate treatment effects by considering settings in which all individuals are assigned a treatment of interest, assuming that an unlimited number of treatment units are available. However, many real-life treatments are of limited supply and cannot be provided to all individuals in the population. For example, patients on the liver transplant waiting list cannot be assigned a liver transplant immediately at the time they reach highest priority because a suitable organ is not likely to be immediately available. In these cases, investigators may still be interested in the effects of treatment strategies in which a finite number of organs are available at a given time, that is, treatment regimes that satisfy resource constraints. Here, we describe an estimand that can be used to define causal effects of treatment strategies that satisfy resource constraints: proportionally-representative interventions for limited resources. We derive a simple class of inverse probability weighted estimators, and apply one such estimator to evaluate the effect of restricting or expanding utilization of "increased risk" liver organs to treat patients with end-stage liver disease. Our method is designed to evaluate policy-relevant interventions in the setting of finite treatment resources
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