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International Journal of Epidemiology
|
December 7, 2018
DAG-informed regression modelling, agent-based modelling and microsimulation modelling: a critical comparison of methods for causal inference
Kellyn F Arnold, Wendy J Harrison, Alison J Heppenstall, et al.
International Journal of Epidemiology
|
March 11, 2020
A causal inference perspective on the analysis of compositional data
Kellyn F Arnold, Laurie Berrie, 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 perspective
Georgia D Tomova, Kellyn F Arnold, Mark S Gilthorpe, et al.
The American Journal of Clinical Nutrition
|
June 22, 2022
Reply to WC Willett et al
Georgia D Tomova, Kellyn F Arnold, Mark S Gilthorpe, et al.
International Journal of Epidemiology
|
June 8, 2021
Analyses of 'change scores' do not estimate causal effects in observational data
Peter W G Tennant, Kellyn F Arnold, George T H Ellison, 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 data
Laurie Berrie, Kellyn F Arnold, Georgia D Tomova, et al.
International Journal of Epidemiology
|
May 8, 2020
Reflection on modern methods: generalized linear models for prognosis and intervention-theory, practice and implications for machine learning
Kellyn F Arnold, Vinny Davies, Marc de Kamps, et al.
Plos One
|
April 14, 2022
Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: A counterfactual modelling study
Kellyn F Arnold, Mark S Gilthorpe, Nisreen A Alwan, et al.
BMC Medical Research Methodology
|
March 23, 2025
Simulating hierarchical data to assess the utility of ecological versus multilevel analyses in obtaining individual-level causal effects
Lydia Kakampakou, Jonathan Stokes, Andreas Hoehn, et al.
The Lancet. Digital Health
|
December 17, 2020
Time to reality check the promises of machine learning-powered precision medicine
Jack Wilkinson, Kellyn F Arnold, Eleanor J Murray, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 11) with videos related to
Sort By:
Page
of 2
International Journal of Epidemiology
|
December 7, 2018
DAG-informed regression modelling, agent-based modelling and microsimulation modelling: a critical comparison of methods for causal inference
Kellyn F Arnold, Wendy J Harrison, Alison J Heppenstall, et al.
International Journal of Epidemiology
|
March 11, 2020
A causal inference perspective on the analysis of compositional data
Kellyn F Arnold, Laurie Berrie, 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 perspective
Georgia D Tomova, Kellyn F Arnold, Mark S Gilthorpe, et al.
The American Journal of Clinical Nutrition
|
June 22, 2022
Reply to WC Willett et al
Georgia D Tomova, Kellyn F Arnold, Mark S Gilthorpe, et al.
International Journal of Epidemiology
|
June 8, 2021
Analyses of 'change scores' do not estimate causal effects in observational data
Peter W G Tennant, Kellyn F Arnold, George T H Ellison, 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 data
Laurie Berrie, Kellyn F Arnold, Georgia D Tomova, et al.
International Journal of Epidemiology
|
May 8, 2020
Reflection on modern methods: generalized linear models for prognosis and intervention-theory, practice and implications for machine learning
Kellyn F Arnold, Vinny Davies, Marc de Kamps, et al.
Plos One
|
April 14, 2022
Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: A counterfactual modelling study
Kellyn F Arnold, Mark S Gilthorpe, Nisreen A Alwan, et al.
BMC Medical Research Methodology
|
March 23, 2025
Simulating hierarchical data to assess the utility of ecological versus multilevel analyses in obtaining individual-level causal effects
Lydia Kakampakou, Jonathan Stokes, Andreas Hoehn, et al.
The Lancet. Digital Health
|
December 17, 2020
Time to reality check the promises of machine learning-powered precision medicine
Jack Wilkinson, Kellyn F Arnold, Eleanor J Murray, et al.
Page
of 2