Zobrazeno 1 - 10
of 428
pro vyhledávání: '"Keogh, Ruth H."'
Autor:
Bonneville, Edouard F., Beyersmann, Jan, Keogh, Ruth H., Bartlett, Jonathan W., Morris, Tim P., Polverelli, Nicola, de Wreede, Liesbeth C., Putter, Hein
The Fine-Gray model for the subdistribution hazard is commonly used for estimating associations between covariates and competing risks outcomes. When there are missing values in the covariates included in a given model, researchers may wish to multip
Externí odkaz:
http://arxiv.org/abs/2405.16602
Many clinical questions involve estimating the effects of multiple treatments using observational data. When using longitudinal data, the interest is often in the effect of treatment strategies that involve sustaining treatment over time. This requir
Externí odkaz:
http://arxiv.org/abs/2405.01110
Autor:
van Geloven, Nan, Keogh, Ruth H, van Amsterdam, Wouter, Cinà, Giovanni, Krijthe, Jesse H., Peek, Niels, Luijken, Kim, Magliacane, Sara, Morzywołek, Paweł, van Ommen, Thijs, Putter, Hein, Sperrin, Matthew, Wang, Junfeng, Weir, Daniala L., Didelez, Vanessa
Prediction models are increasingly proposed for guiding treatment decisions, but most fail to address the special role of treatments, leading to inappropriate use. This paper highlights the limitations of using standard prediction models for treatmen
Externí odkaz:
http://arxiv.org/abs/2402.17366
Autor:
Seaman, Shaun R, Keogh, Ruth H
Marginal structural models (MSMs) are often used to estimate causal effects of treatments on survival time outcomes from observational data when time-dependent confounding may be present. They can be fitted using, e.g., inverse probability of treatme
Externí odkaz:
http://arxiv.org/abs/2309.05025
We use a recently proposed staggered difference-in-differences approach to investigate effects of adoption of an online consultation system in English general practice on antibiotic prescribing patterns. The target estimand is the average effect for
Externí odkaz:
http://arxiv.org/abs/2305.19878
Autor:
Tanner, Kamaryn, Keogh, Ruth H., Coupland, Carol A. C., Hippisley-Cox, Julia, Diaz-Ordaz, Karla
Over time, the performance of clinical prediction models may deteriorate due to changes in clinical management, data quality, disease risk and/or patient mix. Such prediction models must be updated in order to remain useful. Here, we investigate meth
Externí odkaz:
http://arxiv.org/abs/2305.00260
Autor:
Keogh, Ruth H., van Geloven, Nan
Predictions under interventions are estimates of what a person's risk of an outcome would be if they were to follow a particular treatment strategy, given their individual characteristics. Such predictions can give important input to medical decision
Externí odkaz:
http://arxiv.org/abs/2304.10005
Autor:
Bartlett, Jonathan W., Parra, Camila Olarte, Granger, Emily, Keogh, Ruth H., van Zwet, Erik W., Daniel, Rhian M.
G-formula is a popular approach for estimating treatment or exposure effects from longitudinal data that are subject to time-varying confounding. G-formula estimation is typically performed by Monte-Carlo simulation, with non-parametric bootstrapping
Externí odkaz:
http://arxiv.org/abs/2301.12026
Autor:
Palma, Marco, Keogh, Ruth H, Carr, Siobhán B, Szczesniak, Rhonda, Taylor-Robinson, David, Wood, Angela M, Muniz-Terrera, Graciela, Barrett, Jessica K
Publikováno v:
In Journal of Cystic Fibrosis September 2024 23(5):936-942