Výsledky vyhledávání - "Gorbach, Tetiana"

Report

Valid causal inference with unobserved confounding in high-dimensional settings

Autor: Moosavi, Niloofar, Gorbach, Tetiana, de Luna, Xavier

Various methods have recently been proposed to estimate causal effects with confidence intervals that are uniformly valid over a set of data generating processes when high-dimensional nuisance models are estimated by post-model-selection or machine l

Externí odkaz: http://arxiv.org/abs/2401.06564

Zobrazit plný text záznamu

Report

Contrasting Identifying Assumptions of Average Causal Effects: Robustness and Semiparametric Efficiency

Autor: Gorbach, Tetiana, de Luna, Xavier, Karvanen, Juha, Waernbaum, Ingeborg

Publikováno v: Journal of Machine Learning Research 24 (197), 1-65, 2023

Semiparametric inference on average causal effects from observational data is based on assumptions yielding identification of the effects. In practice, several distinct identifying assumptions may be plausible; an analyst has to make a delicate choic

Externí odkaz: http://arxiv.org/abs/2111.15233

Zobrazit plný text záznamu

Akademický článek

No moderating influence of education on the association between changes in hippocampus volume and memory performance in aging

Autor: Lövdén, Martin, Pagin, Amos, Bartrés-Faz, David, Boraxbekk, Carl-Johan, Brandmaier, Andreas M., Demnitz, Naiara, Drevon, Christian A., Ebmeier, Klaus P., Fjell, Anders M., Ghisletta, Paolo, Gorbach, Tetiana, Lindenberger, Ulman, Plachti, Anna, Walhovd, Kristine B., Nyberg, Lars

Publikováno v: In Neurobiology of Aging Science 2023 4

Zobrazit plný text záznamu

Report

Inference for partial correlation when data are missing not at random

Autor: Gorbach, Tetiana, de Luna, Xavier

Publikováno v: Statistics & Probability letters 141 (2018) 82-89

We introduce uncertainty regions to perform inference on partial correlations when data are missing not at random. These uncertainty regions are shown to have a desired asymptotic coverage. Their finite sample performance is illustrated via simulatio

Externí odkaz: http://arxiv.org/abs/1710.04569

Zobrazit plný text záznamu