Results 31 to 40 of about 133,258 (310)

The role of causal inference in health services research II: a framework for causal inference. [PDF]

, 2020
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).
Zwahlen, Marcel, Puhan, Milo A, Moser, André, Puhan, Milo A; https://orcid.org/   +3 more
core   +1 more source

Adverse events associated with COVID-19 vaccination or diagnosis among pregnant and non-pregnant women in the United States, 2021-2022

International Journal of Infectious Diseases
Objectives: To quantify the incidence of adverse events after COVID-19 vaccination and COVID-19 diagnosis in women of reproductive age; to examine pregnancy as a potential risk modifier.
Stacey L. Rowe, Sheena G. Sullivan, Julia J. Koerber, Flor M. Muñoz, Matthew M. Coates, Onyebuchi A. Arah, Annette K. Regan   +6 more
doaj   +1 more source

Estimating Mann–Whitney-Type Causal Effects for Right-Censored Survival Outcomes

Journal of Causal Inference, 2019
Mann–Whitney-type causal effects are clinically relevant, easy to interpret, and readily applicable to a wide range of study settings. This article considers estimation of such effects when the outcome variable is a survival time subject to right ...
Zhang Zhiwei, Liu Chunling, Ma Shujie, Zhang Min   +3 more
doaj   +1 more source

Computational Causal Inference

CoRR, 2020
We introduce computational causal inference as an interdisciplinary field across causal inference, algorithms design and numerical computing. The field aims to develop software specializing in causal inference that can analyze massive datasets with a variety of causal effects, in a performant, general, and robust way.
openaire   +2 more sources

Estimating Causal Effects of New Treatments Despite Self-Selection: The Case of Experimental Medical Treatments

Journal of Causal Inference, 2019
Providing terminally ill patients with access to experimental treatments, as allowed by recent “right to try” laws and “expanded access” programs, poses a variety of ethical questions.
Hazlett Chad
doaj   +1 more source

Bipartite Causal Inference with Interference

Statistical Science, 2021
Statistical methods to evaluate the effectiveness of interventions are increasingly challenged by the inherent interconnectedness of units. Specifically, a recent flurry of methods research has addressed the problem of interference between observations, which arises when one observational unit's outcome depends not only on its treatment but also the ...
Zigler, Corwin M., Papadogeorgou, Georgia   +1 more
openaire   +6 more sources

Causal Inference in Audiovisual Perception [PDF]

The Journal of Neuroscience, 2020
In our natural environment the senses are continuously flooded with a myriad of signals. To form a coherent representation of the world, the brain needs to integrate sensory signals arising from a common cause and segregate signals coming from separate causes.
Mihalik, Agoston, Noppeney, U., Noppeney, U.   +2 more
openaire   +5 more sources

Health‐Related Social Needs in Children With Sickle Cell Disease Are Associated With Worse Health‐Related Quality of Life

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Children with sickle cell disease (SCD) face multiple acute and chronic medical complications that may impact their quality of life as reported by patients themselves. Health‐related social needs (HRSNs), such as food and housing insecurity, are common in people with SCD, but the association between HRSNs and patient‐reported ...
Sarah J. Marks, Molly Sonenklar, Cerelia Donald, Cecelia Valrie, Wally Smith, India Sisler   +5 more
wiley   +1 more source

Women on the ballot and women at the polls: how women's representation shapes voter turnout in local elections

Political Science Research and Methods
We argue that more female candidates on the ballot will decrease the gender participation gap at the polls. We test this hypothesis with data from Italian local elections between 2008 and 2020, taking advantage of a 2012 law requiring at least a third of
Emanuel Coman, Sarah Shair-Rosenfield
doaj   +1 more source

Testing for the Unconfoundedness Assumption Using an Instrumental Assumption

Journal of Causal Inference, 2014
The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption (exogeneity of the treatment) or on the availability of an instrument.
de Luna Xavier, Johansson Per
doaj   +1 more source