Tetiana Gorbach

My research concerns developing statistical methods for analyses with missing data applied to cognitive ageing and dementia research as well as causal inference.

Contact

tetiana.gorbach@umu.se

+46 90 786 72 01

Works as

Associate professor at Umeå School of Business, Economics and Statistics (USBE) Section: Statistics

Samhällsvetarhuset, Biblioteksgränd 6 Umeå universitet, 901 87 Umeå

My ORCID Profile: https://orcid.org/0000-0003-2135-9963

I am the principal investigator of the project: "Selection bias in ageing studies: novel statistical methods for analyses of incomplete datasets" (Fortes international postdoc). 2 300 000 SEK. Project leader. 2022-2023.

Project: "Machine learning to study causality with big datasets: towards methods yielding valid statistical conclusions". Marianne och Marcus Wallenbergs Stilftelse. 6 000 000 SEK. Co-applicant. Project leader: Xavier de Luna. 2022-2027.

Pattern mixture sensitivity analyses via multiple imputations for non-ignorable dropout in joint modeling of cognition and risk of dementia

Statistics in Medicine, John Wiley & Sons 2025, Vol. 44, (6)

Gorbach, Tetiana; Carpenter, James R.; Frost, Chris; et al.

Valid causal inference with unobserved confounding in high-dimensional settings

Journal of Causal Inference, Walter de Gruyter 2025, Vol. 13, (1)

Moosavi, Niloofar; Gorbach, Tetiana; de Luna, Xavier

Contrasting identifying assumptions of average causal effects: robustness and semiparametric efficiency

Journal of machine learning research, Microtome Publishing 2023, Vol. 24, (197) : 1-65

Gorbach, Tetiana; de Luna, Xavier; Waernbaum, Ingeborg; et al.

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

Aging Brain, Elsevier 2023, Vol. 4

Lövdén, Martin; Pagin, Amos; Bartrés-Faz, David; et al.

DyNAMiC: A prospective longitudinal study of dopamine and brain connectomes: A new window into cognitive aging

Journal of Neuroscience Research, John Wiley & Sons 2022, Vol. 100, (6) : 1296-1320

Nordin, Kristin; Gorbach, Tetiana; Pedersen, Robin; et al.

When functional blurring becomes deleterious: Reduced system segregation is associated with less white matter integrity and cognitive decline in aging

NeuroImage, Academic Press 2021, Vol. 242

Pedersen, Robin; Geerligs, Linda; Andersson, Micael; et al.

Physical activity and aerobic fitness in relation to local and interhemispheric functional connectivity in adolescents' brains

Brain and Behavior, John Wiley & Sons 2021, Vol. 11, (2)

Ruotsalainen, Ilona; Glerean, Enrico; Karvanen, Juha; et al.

A Hierarchical Bayesian Mixture Model Approach for Analysis of Resting-State Functional Brain Connectivity: An Alternative to Thresholding

Brain Connectivity, Mary Ann Liebert 2020, Vol. 10, (5) : 202-211

Gorbach, Tetiana; Lundquist, Anders; de Luna, Xavier; et al.

Longitudinal association between hippocampus atrophy and episodic-memory decline in non-demented APOE ε4 carriers

Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, John Wiley & Sons 2020, Vol. 12, (1)

Gorbach, Tetiana; Pudas, Sara; Bartrés-Faz, David; et al.

Physical activity, aerobic fitness, and brain white matter: Their role for executive functions in adolescence

Developmental Cognitive Neuroscience, Elsevier 2020, Vol. 42

Ruotsalainen, Ilona; Gorbach, Tetiana; Perkola, Jaana; et al.

Methods for longitudinal brain imaging studies with dropout

Statistical studies, 54

Gorbach, Tetiana

Aerobic fitness, but not physical activity, is associated with grey matter volume in adolescents

Behavioural Brain Research, Elsevier 2019, Vol. 362 : 122-130

Ruotsalainen, Ilona; Renvall, Ville; Gorbach, Tetiana; et al.

Inference for partial correlation when data are missing not at random

Statistics and Probability Letters, Elsevier 2018, Vol. 141 : 82-89

Gorbach, Tetiana; de Luna, Xavier

Longitudinal association between hippocampus atrophy and episodic-memory decline

Neurobiology of Aging, Vol. 51 : 167-176

Gorbach, Tetiana; Pudas, Sara; Lundquist, Anders; et al.

A Hierarchical Bayesian Mixture Modeling Approach for Analysis of Resting-State Functional Brain Connectivity: An Alternative to Thresholding

Gorbach, Tetiana; Lundquist, Anders; de Luna, Xavier; et al.

Bayesian mixture modeling for longitudinal fMRI connectivity studies with dropout

Gorbach, Tetiana; Lundquist, Anders; de Luna, Xavier; et al.

Valid causal inference: model selection and sensitivity to unobserved confounding in high-dimensional settings

Moosavi, Niloofar; Gorbach, Tetiana; de Luna, Xavier

A note on sensitivity analysis for post-machine learning causal inference

Moosavi, Niloofar; Gorbach, Tetiana; de Luna, Xavier

Physical activity is positively related tolocal functional connectivity in adolescents’ brains

Ruotsalainen, Ilona; Glerean, Enrico; Karvanen, Juha; et al.

View publications in DiVA

Research groups

Group member

Stat4Reg

Research projects

1 January 2025 until 31 December 2028

Generative AI to promote open science in register based research

1 June 2022 until 31 December 2026

Machine learning to study causality with big datasets: towards methods yielding valid statistical conclusions

1 January 2015

DYNAMIC

Published: 03 Jun, 2021

Developing accurate statistical methods

Published: 31 May, 2021

Grants from Forte and Handelsbanken