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Georgia D Tomova

Showing results (1-10 of 7) with videos related to

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The American Journal of Clinical Nutrition|October 12, 2022
Theory and performance of substitution models for estimating relative causal effects in nutritional epidemiologyGeorgia D Tomova, Mark S Gilthorpe, Peter Wg Tennant
American Journal of Epidemiology|January 23, 2026
How can the use of different modes of survey data collection introduce bias? An introduction to mode effects using directed acyclic graphs (DAGs)Georgia D Tomova, Richard J Silverwood, Peter W G Tennant, et al.
The American Journal of Clinical Nutrition|July 27, 2021
Adjustment for energy intake in nutritional research: a causal inference perspectiveGeorgia D Tomova, Kellyn F Arnold, Mark S Gilthorpe, et al.
BMC Medical Research Methodology|April 17, 2025
A comparison of methods for analysing compositional data with fixed and variable totals: a simulation study using the examples of time-use and dietary dataGeorgia D Tomova, Rosemary Walmsley, Laurie Berrie, et al.
American Journal of Epidemiology|June 25, 2024
Depicting deterministic variables within directed acyclic graphs: an aid for identifying and interpreting causal effects involving derived variables and compositional dataLaurie Berrie, Kellyn F Arnold, Georgia D Tomova, et al.
Plos One|April 14, 2022
Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: A counterfactual modelling studyKellyn F Arnold, Mark S Gilthorpe, Nisreen A Alwan, et al.
International Journal of Epidemiology|December 17, 2020
Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendationsPeter W G Tennant, Eleanor J Murray, Kellyn F Arnold, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
The American Journal of Clinical Nutrition|October 12, 2022
Theory and performance of substitution models for estimating relative causal effects in nutritional epidemiologyGeorgia D Tomova, Mark S Gilthorpe, Peter Wg Tennant
American Journal of Epidemiology|January 23, 2026
How can the use of different modes of survey data collection introduce bias? An introduction to mode effects using directed acyclic graphs (DAGs)Georgia D Tomova, Richard J Silverwood, Peter W G Tennant, et al.
The American Journal of Clinical Nutrition|July 27, 2021
Adjustment for energy intake in nutritional research: a causal inference perspectiveGeorgia D Tomova, Kellyn F Arnold, Mark S Gilthorpe, et al.
BMC Medical Research Methodology|April 17, 2025
A comparison of methods for analysing compositional data with fixed and variable totals: a simulation study using the examples of time-use and dietary dataGeorgia D Tomova, Rosemary Walmsley, Laurie Berrie, et al.
American Journal of Epidemiology|June 25, 2024
Depicting deterministic variables within directed acyclic graphs: an aid for identifying and interpreting causal effects involving derived variables and compositional dataLaurie Berrie, Kellyn F Arnold, Georgia D Tomova, et al.
Plos One|April 14, 2022
Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: A counterfactual modelling studyKellyn F Arnold, Mark S Gilthorpe, Nisreen A Alwan, et al.
International Journal of Epidemiology|December 17, 2020
Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendationsPeter W G Tennant, Eleanor J Murray, Kellyn F Arnold, et al.
Pageof 1