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Minimum sample size for developing a multivariable prediction model: Part I – Continuous outcomes

Abstract:

In the medical literature, hundreds of prediction models are being developed to predict health outcomes in individuals. For continuous outcomes, typically a linear regression model is developed to predict an individual's outcome value conditional on values of multiple predictors (covariates). To improve model development and reduce the potential for overfitting, a suitable sample size is required in terms of the number of subjects (n) relative to the number of predictor parameters (p) for pot...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1002/sim.7993

Authors


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ORCID:
0000-0001-8699-0735
Snell, KIE More by this author
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ORCID:
0000-0001-7481-0282
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ORCID:
0000-0003-2803-1151
Harrell, FE More by this author
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Publisher:
Wiley Publisher's website
Journal:
Statistics in Medicine Journal website
Publication date:
2018-10-22
Acceptance date:
2018-09-13
DOI:
EISSN:
1097-0258
ISSN:
0277-6715
Pubs id:
pubs:935170
URN:
uri:3fbc1e5c-b5fe-4123-82b8-8490127cd276
UUID:
uuid:3fbc1e5c-b5fe-4123-82b8-8490127cd276
Local pid:
pubs:935170

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