Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations PWG Tennant, EJ Murray, KF Arnold, L Berrie, MP Fox, SC Gadd, ... International journal of epidemiology 50 (2), 620-632, 2021 | 637 | 2021 |
Adjustment for energy intake in nutritional research: a causal inference perspective GD Tomova, KF Arnold, MS Gilthorpe, PWG Tennant The American journal of clinical nutrition 115 (1), 189-198, 2022 | 91 | 2022 |
Theory and performance of substitution models for estimating relative causal effects in nutritional epidemiology GD Tomova, MS Gilthorpe, PWG Tennant The American Journal of Clinical Nutrition 116 (5), 1379-1388, 2022 | 25 | 2022 |
Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: A counterfactual modelling study KF Arnold, MS Gilthorpe, NA Alwan, AJ Heppenstall, GD Tomova, ... PLoS One 17 (4), e0263432, 2022 | 18 | 2022 |
Reply to WC Willett et al. GD Tomova, KF Arnold, MS Gilthorpe, PWG Tennant The American Journal of Clinical Nutrition 116 (2), 609-610, 2022 | 6 | 2022 |
Depicting deterministic variables within directed acyclic graphs (DAGs): An aid for identifying and interpreting causal effects involving derived variables and compositional data L Berrie, KF Arnold, GD Tomova, MS Gilthorpe, PWG Tennant American Journal of Epidemiology, kwae153, 2024 | 4* | 2024 |
Lord's' paradox'explained: the 50-year warning on the use of'change scores' in observational data PWG Tennant, GD Tomova, EJ Murray, KF Arnold, MP Fox, MS Gilthorpe arXiv preprint arXiv:2302.01822, 2023 | 2* | 2023 |
Meta-analyses of nutritional exposures must identify and distinguish between study estimands: an illustrative review N Ortega, PWG Tennant, CC Dahm, D Tobias, DC Greenwood, DB Ibsen, ... OSF, 2023 | | 2023 |
Causal Inference with Compositional Data: Using directed acyclic graphs and data simulations to understand and model robust causal effects in nutritional and time-use epidemiology GD Tomova University of Leeds, 2023 | | 2023 |