Results 71 to 80 of about 133,258 (310)

Incremental intervention effects in studies with dropout and many timepoints#

Journal of Causal Inference, 2021
Modern longitudinal studies collect feature data at many timepoints, often of the same order of sample size. Such studies are typically affected by dropout and positivity violations.
Kim Kwangho, Kennedy Edward H., Naimi Ashley I.   +2 more
doaj   +1 more source

Comparative Evaluation of Hemodiafiltration, Hemoperfusion, and Standard Hemodialysis on Efficacy, Inflammatory Control, Dialysis Adequacy, and Safety in End‐Stage Renal Disease: A Prospective Observational Study

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo, Weisi Dai, Jie Mao, Mei Ye, Xingshan Lu, Xiaocui Zhang   +5 more
wiley   +1 more source

Causal Inference in Quantum Mechanics: A Reassessment [PDF]

, 2007
There has been an intense discussion, albeit largely an implicit one, concerning the inference of causal hypotheses from statistical correlations in quantum mechanics ever since John Bell’s first statement of his notorious theorem in 1966.
Suárez, Mauricio
core  

Revisiting a Discrepant Result: A Propensity Score Analysis, the Paired Availability Design for Historical Controls, and a Meta-Analysis of Randomized Trials

Journal of Causal Inference, 2013
There is an ongoing controversy over whether epidural analgesia for women in labor increases the probability of Caesarean section. Previous research compared results from three methods for estimating the effect of epidural analgesia on the probability of
G. Baker Stuart, S. Lindeman Karen
doaj   +1 more source

Conditional as-if analyses in randomized experiments

Journal of Causal Inference, 2021
The injunction to “analyze the way you randomize” is well known to statisticians since Fisher advocated for randomization as the basis of inference. Yet even those convinced by the merits of randomization-based inference seldom follow this injunction to ...
Pashley Nicole E., Basse Guillaume W., Miratrix Luke W.   +2 more
doaj   +1 more source

Enteropathogenic E. coli shows delayed attachment and host response in human jejunum organoid‐derived monolayers compared to HeLa cells

FEBS Letters, EarlyView.
Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi, Pilar Samperio Ventayol, Natalie Burkard, Nicolas Schlegel, Carmen Aguilar, Sina Bartfeld   +5 more
wiley   +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

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