Causal inference for evaluating prescription opioid abuse using trend‐in‐trend design
Sign Up to like & getrecommendations! Published in 2019 at "Pharmacoepidemiology and Drug Safety"
DOI: 10.1002/pds.4736
Abstract: One response to the opioid crisis in the United States has been the development of opioid analgesics with properties intended to reduce non‐oral use. Previous evaluations of abuse in the community have relied on population… read more here.
Keywords: trend; trend trend; causal inference; opioid ... See more keywords
Using a monotone single-index model to stabilize the propensity score in missing data problems and causal inference.
Sign Up to like & getrecommendations! Published in 2019 at "Statistics in medicine"
DOI: 10.1002/sim.8048
Abstract: The augmented inverse weighting method is one of the most popular methods for estimating the mean of the response in causal inference and missing data problems. An important component of this method is the propensity… read more here.
Keywords: model; single index; propensity score; causal inference ... See more keywords
A flexible approach for causal inference with multiple treatments and clustered survival outcomes
Sign Up to like & getrecommendations! Published in 2022 at "Statistics in Medicine"
DOI: 10.1002/sim.9548
Abstract: When drawing causal inferences about the effects of multiple treatments on clustered survival outcomes using observational data, we need to address implications of the multilevel data structure, multiple treatments, censoring, and unmeasured confounding for causal… read more here.
Keywords: causal inference; treatments clustered; causal; multiple treatments ... See more keywords
Robust causal inference of drug‐drug interactions
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DOI: 10.1002/sim.9653
Abstract: There is growing interest in developing causal inference methods for multi‐valued treatments with a focus on pairwise average treatment effects. Here we focus on a clinically important, yet less‐studied estimand: causal drug‐drug interactions (DDIs), which… read more here.
Keywords: propensity score; causal inference; robust causal; drug interactions ... See more keywords
Causal inference in survival analysis under deterministic missingness of confounders in register data
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DOI: 10.1002/sim.9706
Abstract: Long‐term register data offer unique opportunities to explore causal effects of treatments on time‐to‐event outcomes, in well‐characterized populations with minimum loss of follow‐up. However, the structure of the data may pose methodological challenges. Motivated by… read more here.
Keywords: causal inference; missingness; survival; entry date ... See more keywords
Methods and tools for causal discovery and causal inference
Sign Up to like & getrecommendations! Published in 2022 at "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"
DOI: 10.1002/widm.1449
Abstract: Causality is a complex concept, which roots its developments across several fields, such as statistics, economics, epidemiology, computer science, and philosophy. In recent years, the study of causal relationships has become a crucial part of… read more here.
Keywords: causal inference; methods tools; discovery causal; tools causal ... See more keywords
The role of causal inference in health services research II: a framework for causal inference
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Public Health"
DOI: 10.1007/s00038-020-01334-1
Abstract: In a previous Hints and Kinks, we discussed the role of causal inference in tasks of health services research (HSR) using examples from health system interventions (Moser et al. 2020). In the present Hints and… read more here.
Keywords: health; role causal; causal inference; causal ... See more keywords
Origo: causal inference by compression
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DOI: 10.1007/s10115-017-1130-5
Abstract: Causal inference from observational data is one of the most fundamental problems in science. In general, the task is to tell whether it is more likely that $$X$$X caused $$Y$$Y, or vice versa, given only… read more here.
Keywords: origo causal; inference compression; causal inference; inference ... See more keywords
Preventive Effect Heterogeneity: Causal Inference in Personalized Prevention
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DOI: 10.1007/s11121-017-0826-9
Abstract: This paper employs a causal inference framework to explore two logically distinct forms of preventive effect heterogeneity relevant for studying variation in preventive effect as a basis for developing more personalized interventions. Following VanderWeele (2015),… read more here.
Keywords: preventive effect; effect heterogeneity; causal inference; inference ... See more keywords
How we (should?) study Congress and history
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DOI: 10.1007/s11127-019-00693-5
Abstract: Applying an array of quasi-experimental designs, proponents of causal inference approaches to studying American politics are setting their sights on the study of Congress. In many ways, that focus makes sense: improved research design allows… read more here.
Keywords: study congress; congress history; causal inference;
Doubly robust estimation of the causal effects in the causal inference with missing outcome data
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-018-0957-2
Abstract: The goal of this article is to attempt to develop doubly robust (DR) estimator in the causal inference with ignorable missing outcome data. In the causal inference with missing outcome data, an estimator is doubly… read more here.
Keywords: outcome data; estimator; causal inference; missing outcome ... See more keywords