Results 81 to 90 of about 1,239,696 (252)

Sensitivity analyses for robust causal inference from Mendelian randomization analyses with multiple genetic variants

Epidemiology, 2016
Mendelian randomization investigations are becoming more powerful and simpler to perform, due to the increasing size and coverage of genome-wide association studies and the increasing availability of summarized data on genetic associations with risk ...
S. Burgess, J. Bowden, T. Fall, E. Ingelsson, S. Thompson   +4 more
semanticscholar   +1 more source

Causal inference in cplint

International Journal of Approximate Reasoning, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Riguzzi, Fabrizio, Cota, Giuseppe, Bellodi, Elena, Zese, Riccardo   +3 more
openaire   +3 more sources

Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate

Journal of Causal Inference, 2015
In the Regression Discontinuity (RD) design, units are assigned a treatment based on whether their value of an observed covariate is above or below a fixed cutoff.
Cattaneo Matias D., Frandsen Brigham R., Titiunik Rocío   +2 more
doaj   +1 more source

Novel bounds for causal effects based on sensitivity parameters on the risk difference scale

Journal of Causal Inference, 2021
Unmeasured confounding is an important threat to the validity of observational studies. A common way to deal with unmeasured confounding is to compute bounds for the causal effect of interest, that is, a range of values that is guaranteed to include the ...
Sjölander Arvid, Hössjer Ola
doaj   +1 more source

Inferring causality [PDF]

Journal of Vascular Surgery, 2020
Daniel J, Wong, Elliot L, Chaikof
openaire   +2 more sources

Causal Markov, Robustness and the Quantum Correlations [PDF]

, 2009
It is still a matter of controversy whether the Principle of the Common Cause (PCC) can be used as a basis for sound causal inference. It is thus to be expected that its application to quantum mechanics should be a correspondingly controversial issue ...
San Pedro, Iñaki, Suárez, Mauricio, Mauricio Suárez, Iñaki San Pedro   +3 more
core   +1 more source

Targeting mediating mechanisms of social disparities with an interventional effects framework, applied to the gender pay gap in Western Germany

Journal of Causal Inference
The Oaxaca-Blinder (OB) decomposition is a widely used method to explain social disparities. However, assigning causal meaning to its estimated components requires strong assumptions that often lack explicit justification.
Didden Christiane
doaj   +1 more source

To Adjust or Not to Adjust? Sensitivity Analysis of M-Bias and Butterfly-Bias

Journal of Causal Inference, 2015
“M-Bias,” as it is called in the epidemiologic literature, is the bias introduced by conditioning on a pretreatment covariate due to a particular “M-Structure” between two latent factors, an observed treatment, an outcome, and a “collider.” This ...
Ding Peng, Miratrix Luke W.
doaj   +1 more source

Role of placebo samples in observational studies

Journal of Causal Inference
In an observational study, it is common to leverage known null effects to detect bias. One such strategy is to set aside a placebo sample – a subset of data immune from the hypothesized cause-and-effect relationship. Existence of an effect in the placebo
Ye Ting, He Qijia, Chen Shuxiao, Zhang Bo   +3 more
doaj   +1 more source

Design and Analysis of Experiments in Networks: Reducing Bias from Interference

Journal of Causal Inference, 2016
Estimating the effects of interventions in networks is complicated due to interference, such that the outcomes for one experimental unit may depend on the treatment assignments of other units.
Eckles Dean, Karrer Brian, Ugander Johan
doaj   +1 more source