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Validation in prediction research: the waste by data splitting

Journal of clinical epidemiology, 2018-11, Vol.103, p.131-133

Steyerberg, Ewout W.

2018

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Prediction, Not Association, Paves the Road to Precision Medicine

JAMA psychiatry (Chicago, Ill.), 2021-02, Vol.78 (2), p.127

2021

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Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests

BMJ (Online), 2016-01, Vol.352, p.i6

2016

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Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable

BMC medical research methodology, 2012-06, Vol.12 (1), p.82-82, Article 82

2012

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Prediction models need appropriate internal, internal–external, and external validation

Journal of clinical epidemiology, 2016-01, Vol.69, p.245-247

2016

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Towards better clinical prediction models: seven steps for development and an ABCD for validation

European heart journal, 2014-08, Vol.35 (29), p.1925-1931

2014

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Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study

PLoS medicine, 2017-04, Vol.14 (4), p.e1002277-e1002277

2017

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The number of subjects per variable required in linear regression analyses

Journal of clinical epidemiology, 2015-06, Vol.68 (6), p.627-636

2015

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Events per variable (EPV) and the relative performance of different strategies for estimating the out-of-sample validity of logistic regression models

Statistical methods in medical research, 2017-04, Vol.26 (2), p.796-808

2017

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Risk Factors and Outcomes for Postoperative Delirium after Major Surgery in Elderly Patients

PloS one, 2015-08, Vol.10 (8), p.e0136071-e0136071

2015

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Prognosis Research Strategy (PROGRESS) 3: prognostic model research

PLoS medicine, 2013-02, Vol.10 (2), p.e1001381-e1001381

2013

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Graphical assessment of internal and external calibration of logistic regression models by using loess smoothers

Statistics in medicine, 2014-02, Vol.33 (3), p.517-535

2014

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The Integrated Calibration Index (ICI) and related metrics for quantifying the calibration of logistic regression models

Statistics in medicine, 2019-09, Vol.38 (21), p.4051-4065

2019

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A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models

Journal of clinical epidemiology, 2019-06, Vol.110, p.12-22

2019

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A calibration hierarchy for risk models was defined: from utopia to empirical data

Journal of clinical epidemiology, 2016-06, Vol.74, p.167-176

2016

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Prognosis Research Strategy (PROGRESS) 2: prognostic factor research

PLoS medicine, 2013-02, Vol.10 (2), p.e1001380-e1001380

2013

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Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects

BMJ (Online), 2018-12, Vol.363, p.k4245

2018

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Reporting and methods in clinical prediction research: a systematic review

PLoS medicine, 2012-05, Vol.9 (5), p.1-12

2012

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Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators

European urology, 2018-12, Vol.74 (6), p.796-804

2018

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There is no such thing as a validated prediction model

BMC medicine, 2023-02, Vol.21 (1), p.70-70, Article 70

2023

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Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints

BMC medical research methodology, 2014-12, Vol.14 (1), p.137-137, Article 137

2014

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Is the readmission rate a valid quality indicator? A review of the evidence

PloS one, 2014-11, Vol.9 (11), p.e112282-e112282

2014

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Calibration: the Achilles heel of predictive analytics

BMC medicine, 2019-12, Vol.17 (1), p.230-230, Article 230

2019

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Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers

Statistics in medicine, 2011-01, Vol.30 (1), p.11-21

2011

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Validation in prediction research: the waste by data splitting

Prediction, Not Association, Paves the Road to Precision Medicine

Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable

Prediction models need appropriate internal, internal–external, and external validation

Towards better clinical prediction models: seven steps for development and an ABCD for validation

Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study

The number of subjects per variable required in linear regression analyses

Events per variable (EPV) and the relative performance of different strategies for estimating the out-of-sample validity of logistic regression models

Risk Factors and Outcomes for Postoperative Delirium after Major Surgery in Elderly Patients

Prognosis Research Strategy (PROGRESS) 3: prognostic model research

Graphical assessment of internal and external calibration of logistic regression models by using loess smoothers

The Integrated Calibration Index (ICI) and related metrics for quantifying the calibration of logistic regression models

A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models

A calibration hierarchy for risk models was defined: from utopia to empirical data

Prognosis Research Strategy (PROGRESS) 2: prognostic factor research

Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects

Reporting and methods in clinical prediction research: a systematic review

Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators

Derivation and validation of the predicting bleeding complications in patients undergoing stent implantation and subsequent dual antiplatelet therapy (PRECISE-DAPT) score: a pooled analysis of individual-patient datasets from clinical trials

There is no such thing as a validated prediction model

Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints

Is the readmission rate a valid quality indicator? A review of the evidence

Calibration: the Achilles heel of predictive analytics

Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers

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