Calculating the sample size required for developing a clinical prediction model

PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration

(2019) Karel G.M. Moons et al.   ANNALS OF INTERNAL MEDICINE

PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies

(2019) Robert F. Wolff et al.   ANNALS OF INTERNAL MEDICINE

Sample size considerations and predictive performance of multinomial logistic prediction models

(2019) Valentijn M. T. de Jong et al.   STATISTICS IN MEDICINE

A guide to systematic review and meta-analysis of prognostic factor studies

(2019) Richard D Riley et al.   BMJ-British Medical Journal

Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data

(2019) Mohammed T Hudda et al.   BMJ-British Medical Journal

Variable selection - A review and recommendations for the practicing statistician

(2018) Georg Heinze et al.   BIOMETRICAL JOURNAL

Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes

(2018) Richard D Riley et al.   STATISTICS IN MEDICINE

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

(2018) Richard D. Riley et al.   STATISTICS IN MEDICINE

Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study

(2017) Julia Hippisley-Cox et al.   BMJ-British Medical Journal

A guide to systematic review and meta-analysis of prediction model performance

(2017) Thomas P A Debray et al.   BMJ-British Medical Journal

Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study

(2017) Julia Hippisley-Cox et al.   BMJ-British Medical Journal

A guide to systematic review and meta-analysis of prediction model performance

(2017) Thomas P A Debray et al.   BMJ-British Medical Journal

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis

(2016) Maarten van Smeden et al.   BMC Medical Research Methodology

Prediction of risk of recurrence of venous thromboembolism following treatment for a first unprovoked venous thromboembolism: systematic review, prognostic model and clinical decision rule, and economic evaluation

(2016) Joie Ensor et al.   HEALTH TECHNOLOGY ASSESSMENT

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

(2016) Ewout W. Steyerberg et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Adequate sample size for developing prediction models is not simply related to events per variable

(2016) Emmanuel O. Ogundimu et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

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

(2016) Ben Van Calster et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

A closed testing procedure to select an appropriate method for updating prediction models

(2016) Yvonne Vergouwe et al.   STATISTICS IN MEDICINE

Systematic review of prognostic models for recurrent venous thromboembolism (VTE) post-treatment of first unprovoked VTE

(2016) Joie Ensor et al.   BMJ Open

External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges

(2016) Richard D Riley et al.   BMJ-British Medical Journal

Sparse data bias: a problem hiding in plain sight

(2016) Sander Greenland et al.   BMJ-British Medical Journal

External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges

(2016) Richard D Riley et al.   BMJ-British Medical Journal

Sparse data bias: a problem hiding in plain sight

(2016) Sander Greenland et al.   BMJ-British Medical Journal

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration

(2015) Karel G.M. Moons et al.   ANNALS OF INTERNAL MEDICINE

Discrimination-based sample size calculations for multivariable prognostic models for time-to-event data

(2015) Rachel C. Jinks et al.   BMC Medical Research Methodology

A simulation study of sample size demonstrated the importance of the number of events per variable to develop prediction models in clustered data

(2015) L. Wynants et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

The number of subjects per variable required in linear regression analyses

(2015) Peter C. Austin et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Sample size considerations for the external validation of a multivariable prognostic model: a resampling study

(2015) Gary S. Collins et al.   STATISTICS IN MEDICINE

How to develop a more accurate risk prediction model when there are few events

(2015) Menelaos Pavlou et al.   BMJ-British Medical Journal

Individual Participant Data (IPD) Meta-analyses of Diagnostic and Prognostic Modeling Studies: Guidance on Their Use

(2015) Thomas P. A. Debray et al.   PLOS MEDICINE

How to develop a more accurate risk prediction model when there are few events

(2015) Menelaos Pavlou et al.   BMJ-British Medical Journal

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

(2015) Tjeerd van der Ploeg et al.   BMC Medical Research Methodology

Risk prediction with machine learning and regression methods

(2014) Ewout W. Steyerberg et al.   BIOMETRICAL JOURNAL

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

(2014) Peter C Austin et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Meta-analysis and aggregation of multiple published prediction models

(2014) Thomas P.A. Debray et al.   STATISTICS IN MEDICINE

Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research

(2013) Ewout W. Steyerberg et al.   PLOS MEDICINE

Incorporating published univariable associations in diagnostic and prognostic modeling

(2012) Thomas P A Debray et al.   BMC Medical Research Methodology

Aggregating published prediction models with individual participant data: a comparison of different approaches

(2012) Thomas P.A. Debray et al.   STATISTICS IN MEDICINE

Stability Investigations of Multivariable Regression Models Derived from Low- and High-Dimensional Data

(2011) Willi Sauerbrei et al.   Journal of Biopharmaceutical Statistics

Performance of logistic regression modeling: beyond the number of events per variable, the role of data structure

(2011) Delphine S. Courvoisier et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Sample Size Planning for Statistical Power and Accuracy in Parameter Estimation

(2007) Scott E. Maxwell et al.   Annual Review of Psychology