Results 21 to 30 of about 879,103 (205)
REndo: Internal Instrumental Variables to Address Endogeneity
Journal of Statistical Software, 2023 Endogeneity is a common problem in any causal analysis. It arises when the independence assumption between an explanatory variable and the error in a statistical model is violated.
Raluca Gui +3 more
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Effect of hospital assignment on mortality for AMI patients
BMC Health Services Research, 2023 Background International guidelines recommend percutaneous coronary intervention (PCI) to treat acute myocardial infarction (AMI) if PCI can be performed within two hours.
Mari Grøsland +2 more
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Econometrics, 2017 Swamy et al. (2015) argue that valid instruments cannot exist when a structural model is misspecified. This note shows that this is not true in general. In simple examples valid instruments can exist and can help to estimate parameters of interest.
Burkhard Raunig
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IET Control Theory & Applications, 2021 Feedforward control has been widely used to improve the tracking performance of precision motion systems. This paper develops a new data‐driven feedforward tuning approach associated with rational basis functions.
Weicai Huang +3 more
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Frontiers in Microbiology, 2023 IntroductionPrevious research has reported that the gut microbiota performs an essential role in sleep through the microbiome–gut–brain axis. However, the causal association between gut microbiota and sleep remains undetermined.MethodsWe performed a two ...
Jun Wu +9 more
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Frontiers in Genetics, 2023 Background: High dimensional mediation analysis is frequently conducted to explore the role of epigenetic modifiers between exposure and health outcome.
Fangyao Chen +7 more
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Instrumental variable models for discrete outcomes [PDF]
, 2008 Single equation instrumental variable models for discrete outcomes are shown to be set not point identifying for the structural functions that deliver the values of the discrete outcome.
Chesher, A.
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An introduction to instrumental variable assumptions, validation and estimation
Emerging Themes in Epidemiology, 2018 The instrumental variable method has been employed within economics to infer causality in the presence of unmeasured confounding. Emphasising the parallels to randomisation may increase understanding of the underlying assumptions within epidemiology.
Mette Lise Lousdal
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Frontiers in Genetics, 2021 BackgroundIn epidemiological studies, it has been proven that the occurrence of type 2 diabetes mellitus (T2DM) is related to an increased risk of infectious diseases.
Huachen Wang +5 more
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Journal of Causal Inference, 2016 An instrumental variable can be used to test the causal null hypothesis that an exposure has no causal effect on the outcome, by assessing the association between the instrumental variable and the outcome.
Burgess Stephen, Small Dylan S.
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