An Introduction to Causal Inference This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statis... J Pearl - 《Nephron Clinical Practice》 被引量: 243发表: 2010年 Causal Inference in Public Health Causal ...
Alternatives to randomisation in the evaluation of public-health interventions: statistical analysis and causal inference Background: In non-randomised evaluations of public-health interventions, statistical methods to control confounding will usually be required. We review ap... S Cousens,J Hargreaves,C...
We propose that including PGSs in a health disparity measure approach, and causal inference-based methods more broadly, is a valuable addition to the study of gene-environment interplay in complex health outcomes.doi:10.1007/s10654-023-00980-yMoritz Herle...
RCTs have long been thought to be the fundamental basis for demonstrating causal inference. However, in medicine, they may be impractical since clinical trials of intervention take a long time and the results observed may not be what the doctor would expect. Population availability, cost, ...
Causal Inference: What If: Boca Raton: Chapman & Hall/CRC. Google Scholar Hirvonen and Headey, 2018 Kalle Hirvonen, Derek Headey Can governments promote homestead gardening at scale? Evidence from Ethiopia Global Food Security, 19 (2018), pp. 40-47, 10.1016/j.gfs.2018.09.001 Google ...
RCTs reporting one or more observable measure of physical performance related to frailty criteria (e.g. gait speed, grip strength, physical activity levels, mobility, balance, muscle mass, body mass index) as this study design generally supports greater validity and causal inference [40].3...
the use of masks to prevent the spread of SARS-CoV-2. We arrived at this conclusion by merging two different traditions: causal inference and regularized regression. We believe that the union of these techniques will be fruitful in other contexts where the causes and effects are sparse in ...
Design and Analysis of Experiments in Networks: Reducing Bias from Interference Estimating the effects of interventions in networks is complicated due to interference, such that the outcomes for one experimental unit may depend on the ... E Dean,K Brian,U Johan - 《Journal of Causal Inference》...
Hypothetical estimands in clinical trials: a unification of causal inference and missing data methods. Arxiv - Stat Methodol. 2021. Eysenbach G, Group C-E. CONSORT-EHEALTH: improving and standardizing evaluation reports of web-based and mobile health interventions. J Med Internet Res. 2011;13:...
Concepts concerning mediation in the causal inference literature are reviewed. Notions of direct and indirect effects from a counterfactual approach to mediation are compared with those arising from the standard regression approach to mediation of Baron and Kenny (1986), commonly utilized in the social...