Avoiding overadjustment bias in social epidemiology through appropriate covariate selection: a primer

Autor: Anita van Zwieten, Peter W.G. Tennant, Michelle Kelly-Irving, Fiona M. Blyth, Armando Teixeira-Pinto, Saman Khalatbari-Soltani

Publikováno v: Journal of clinical epidemiology. 149

Obtaining accurate estimates of the causal effects of socioeconomic position (SEP) on health is important for public health interventions. To do this, researchers must identify and adjust for all potential confounding variables, while avoiding inappr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6eb92ab7a2fa579c61cea683eb1176a3
https://pubmed.ncbi.nlm.nih.gov/35662623

OP82 Performance of substitution models in nutritional epidemiology

Autor: Georgia D Tomova, Mark S. Gilthorpe, Kellyn F Arnold, Peter W.G. Tennant

Publikováno v: SSM Annual Scientific Meeting.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1de33fa47706ea5dbe9217fd1d740077
https://doi.org/10.1136/jech-2021-ssmabstracts.82

P93 The dangers of causally unaware ethical frameworks for health data

Autor: Mark S. Gilthorpe, Georgia D Tomova, Peter W.G. Tennant, Gabriela Arriagada Bruneau

Publikováno v: SSM Annual Scientific Meeting.

BackgroundDuring the COVID-19 pandemic we have seen various disastrous approaches regarding the use an implementation of measures and studies that performed on past and current health data. Accordingly, in this study, we criticize the lack of concept

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::702a39370fe70ea7233e863ef0744f5d
https://doi.org/10.1136/jech-2021-ssmabstracts.179

Time to reality check the promises of machine learning-powered precision medicine

Autor: Andrew L. Beam, Kellyn F Arnold, Kareem Carr, Peter W.G. Tennant, Maarten van Smeden, Christoph Lippert, Jack Wilkinson, Marc de Kamps, Rachel Sippy, Eleanor J Murray, Mark S. Gilthorpe, Stefan Konigorski

Publikováno v: The Lancet: Digital Health, Vol 2, Iss 12, Pp e677-e680 (2020)
Wilkinson, J, Arnold, K, Murray, E, van Smeden, M, Carr, K, Sippy, R, de Kamps, M, Beam, A, Konigorski, S, Lippert, C, Gilthorpe, M & Tennant, P 2020, ' Time to reality check the promises of machine learning-powered precision medicine ', The Lancet Digital Health, vol. 2, no. 12 . https://doi.org/10.1016/S2589-7500(20)30200-4

Summary: Machine learning methods, combined with large electronic health databases, could enable a personalised approach to medicine through improved diagnosis and prediction of individual responses to therapies. If successful, this strategy would re

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::306bdda7c112c15d13d5154be90e7a9f
https://eprints.whiterose.ac.uk/167291/1/1-s2.0-S2589750020302004-main.pdf

The utility of multilevel models for continuous-time feature selection of spatio-temporal networks

Autor: Alexis Comber, Mark S. Gilthorpe, Peter W.G. Tennant, Sarah C. Gadd, Alison J. Heppenstall

Publikováno v: Computers, Environment and Urban Systems. 91:101728

Many models for the analysis of spatio-temporal networks specify time as a series of discrete steps. This either requires evenly spaced measurement times or the aggregation of data into measurement windows. This can lead to the introduction of bias.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::98705662f6616514a189b910eec2bc5f
https://doi.org/10.1016/j.compenvurbsys.2021.101728