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A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes

Abstract:

It is widely recommended that any developed—diagnostic or prognostic—prediction model is externally validated in terms of its predictive performance measured by calibration and discrimination. When multiple validations have been performed, a systematic review followed by a formal meta-analysis helps to summarize overall performance across multiple settings, and reveals under which circumstances the model performs suboptimal (alternative poorer) and may need adjustment. We discuss how to under...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1177/0962280218785504

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Role:
Author
ORCID:
0000-0002-1790-2719
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Role:
Author
ORCID:
0000-0001-9373-6591
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Publisher:
SAGE Publications Publisher's website
Journal:
Statistical Methods in Medical Research Journal website
Volume:
28
Issue:
9
Pages:
2768-2786
Publication date:
2018-07-23
Acceptance date:
2018-04-30
DOI:
EISSN:
1477-0334
ISSN:
0962-2802
Pmid:
30032705
Source identifiers:
894208
Language:
English
Keywords:
Pubs id:
pubs:894208
UUID:
uuid:3cc5d25a-964c-4c6a-bde5-a0a812acadf8
Local pid:
pubs:894208
Deposit date:
2018-09-04

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