1 citations · 1 across the 2 of their papers we have counts for
4 papers · 1 filter
mecor: An R package for measurement error correction in linear regression models with a continuous outcome
Linda Nab, Maarten van Smeden, Ruth H. Keogh +1
Measurement error in a covariate or the outcome of regression models is common, but is often ignored, even though measurement error can lead to substantial bias in the estimated co…
Comparing methods addressing multi-collinearity when developing prediction models
Artuur M. Leeuwenberg, Maarten van Smeden, Johannes A. Langendijk +5
Clinical prediction models are developed widely across medical disciplines. When predictors in such models are highly collinear, unexpected or spurious predictor-outcome associatio…
On the variability of regression shrinkage methods for clinical prediction models: simulation study on predictive performance
Ben Van Calster, Maarten van Smeden, Ewout W. Steyerberg
When developing risk prediction models, shrinkage methods are recommended, especially when the sample size is limited. Several earlier studies have shown that the shrinkage of mode…
Measurement error in continuous endpoints in randomised trials: problems and solutions
Linda Nab, Rolf H. H. Groenwold, Paco M. J. Welsing +1
In randomised trials, continuous endpoints are often measured with some degree of error. This study explores the impact of ignoring measurement error, and proposes methods to impro…