Zobrazeno 1 - 10
of 1 150
pro vyhledávání: '"Martin, Glen"'
Autor:
Riley, Richard D, Collins, Gary S, Whittle, Rebecca, Archer, Lucinda, Snell, Kym IE, Dhiman, Paula, Kirton, Laura, Legha, Amardeep, Liu, Xiaoxuan, Denniston, Alastair, Harrell Jr, Frank E, Wynants, Laure, Martin, Glen P, Ensor, Joie
When developing a clinical prediction model, the sample size of the development dataset is a key consideration. Small sample sizes lead to greater concerns of overfitting, instability, poor performance and lack of fairness. Previous research has outl
Externí odkaz:
http://arxiv.org/abs/2407.09293
Autor:
Gehringer, Celina K, Martin, Glen P, Van Calster, Ben, Hyrich, Kimme L, Verstappen, Suzanne M M, Sergeant, Jamie C
Multinomial prediction models (MPMs) have a range of potential applications across healthcare where the primary outcome of interest has multiple nominal or ordinal categories. However, the application of MPMs is scarce, which may be due to the added
Externí odkaz:
http://arxiv.org/abs/2312.12008
Autor:
Pate, Alexander, Sperrin, Matthew, Riley, Richard D., Peek, Niels, Van Staa, Tjeerd, Sergeant, Jamie C., Mamas, Mamas A., Lip, Gregory Y. H., Flaherty, Martin O, Barrowman, Michael, Buchan, Iain, Martin, Glen P.
Introduction. There is currently no guidance on how to assess the calibration of multistate models used for risk prediction. We introduce several techniques that can be used to produce calibration plots for the transition probabilities of a multistat
Externí odkaz:
http://arxiv.org/abs/2308.13394
Autor:
Pate, Alexander, Riley, Richard D, Collins, Gary S, van Smeden, Maarten, Van Calster, Ben, Ensor, Joie, Martin, Glen P
Multinomial logistic regression models allow one to predict the risk of a categorical outcome with more than 2 categories. When developing such a model, researchers should ensure the number of participants (n) is appropriate relative to the number of
Externí odkaz:
http://arxiv.org/abs/2207.12892
Background: Existing guidelines for handling missing data are generally not consistent with the goals of prediction modelling, where missing data can occur at any stage of the model pipeline. Multiple imputation (MI), often heralded as the gold stand
Externí odkaz:
http://arxiv.org/abs/2206.12295
Autor:
Jeanselme, Vincent, Martin, Glen, Peek, Niels, Sperrin, Matthew, Tom, Brian, Barrett, Jessica
Observational data in medicine arise as a result of the complex interaction between patients and the healthcare system. The sampling process is often highly irregular and itself constitutes an informative process. When using such data to develop pred
Externí odkaz:
http://arxiv.org/abs/2205.13481
Autor:
Gehringer, Celina K., Martin, Glen P., Van Calster, Ben, Hyrich, Kimme L., Verstappen, Suzanne M.M., Sergeant, Jamie C.
Publikováno v:
In Journal of Clinical Epidemiology October 2024 174
Autor:
Ayayo, Sharon A., Kontopantelis, Evangelos, Martin, Glen P., Zghebi, Salwa S., Taxiarchi, Vicky P., Mamas, Mamas A.
Publikováno v:
In International Journal of Cardiology 1 October 2024 412