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Impact of measurement error and sample size on the performance of multivariable risk prediction models: a simulation study

Abstract:

Risk prediction models, developed to estimate the probability of an individual developing a particular outcome, are frequently published. Few are adequately validated resulting in a large number of prediction models not used in practice. Data are often measured with some degree of error. This error can influence the performance of a prediction model. The impact of either random or systematic error in a particular covariate, the covariate’s strength or the sample size at which this measurement...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted manuscript

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Institution:
University of Oxford
Department:
Oxford, MSD, NDORMS, CSM
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, NDORMS, CSM
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, Primary Care Health Sciences
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, NDORMS, CSM
National Institute for Health Research More from this funder
Publisher:
Society for Academic Primary Care Publisher's website
Publication date:
2017-07-14
Acceptance date:
2017-04-12
Pubs id:
pubs:693639
URN:
uri:bbcb78e2-041d-4335-84f7-073f9e540563
UUID:
uuid:bbcb78e2-041d-4335-84f7-073f9e540563
Local pid:
pubs:693639

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