Comparing risk prediction models.

Comparing risk prediction models.

Bibliografiske detaljer
Main Authors:	Collins, G, Moons, K
Format:	Journal article
Sprog:	English
Udgivet:	2012

Lignende værker

Comparing risk prediction models: Should be routine when deriving a new model for the same purpose
af: Collins, G, et al.
Udgivet: (2012)

Reporting of artificial intelligence prediction models
af: Collins, G, et al.
Udgivet: (2019)

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement.
af: Collins, G, et al.
Udgivet: (2015)

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement
af: Collins, G, et al.
Udgivet: (2015)

Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement.
af: Collins, G, et al.
Udgivet: (2014)

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) : the TRIPOD statement
af: Collins, G, et al.
Udgivet: (2015)

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) : the TRIPOD statement
af: Collins, G, et al.
Udgivet: (2015)

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement.
af: Collins, G, et al.
Udgivet: (2015)

Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement.
af: Collins, G, et al.
Udgivet: (2015)

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement
af: Collins, G, et al.
Udgivet: (2015)

PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration
af: Moons, K, et al.
Udgivet: (2019)

Cardiovascular disease risk prediction in the UK: Which is the best risk prediction model?
af: Collins, G
Udgivet: (2013)

PROBAST: A tool to assess the risk of bias and applicability of prediction model studies
af: Wolff, RF, et al.
Udgivet: (2019)

Risk prediction models: II. External validation, model updating, and impact assessment.
af: Moons, K, et al.
Udgivet: (2012)

Risk prediction models: II. External validation, model updating, and impact assessment
af: Moons, K, et al.
Udgivet: (2012)

Minimum sample size for developing a multivariable prediction model: Part I – Continuous outcomes
af: Riley, R, et al.
Udgivet: (2018)

A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes
af: Debray, T, et al.
Udgivet: (2018)

Minimum sample size for developing a multivariable prediction model: PART II ‐ binary and time‐to‐event outcomes
af: Riley, R, et al.
Udgivet: (2018)

External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges
af: Riley, R, et al.
Udgivet: (2016)

Interpretation of CVD risk predictions in clinical practice: Mission impossible?
af: G R Lagerweij, et al.
Udgivet: (2019-01-01)

Prediction models for cardiovascular disease risk in the general population: systematic review
af: Damen, J, et al.
Udgivet: (2016)

Sample size for binary logistic prediction models: Beyond events per variable criteria
af: Van Smeden, M, et al.
Udgivet: (2018)

Critical appraisal and data extraction for systematic reviews of prediction modelling studies : the CHARMS checklist
af: Moons, K, et al.
Udgivet: (2014)

Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
af: Andaur Navarro, CL, et al.
Udgivet: (2021)

Multivariable risk prediction models: it's all about the performance.
af: Collins, G, et al.
Udgivet: (2013)

Statistical Primer: Developing and validating a risk prediction model
af: Grant, S, et al.
Udgivet: (2018)

A new community for those involved and interested in diagnosis and prognosis
af: Moons, K, et al.
Udgivet: (2017)

Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker
af: Moons, K, et al.
Udgivet: (2012)

Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker.
af: Moons, K, et al.
Udgivet: (2012)

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration.
af: Moons, K, et al.
Udgivet: (2015)

Uniformity in measuring adherence to reporting guidelines: the example of TRIPOD for assessing completeness of reporting of prediction model studies
af: Heus, P, et al.
Udgivet: (2019)

Poor reporting of multivariable prediction model studies: towards a targeted implementation strategy of the TRIPOD statement
af: Heus, P, et al.
Udgivet: (2018)

Calculating the sample size required for developing a clinical prediction model
af: Riley, RD, et al.
Udgivet: (2020)

Transparent reporting of multivariable prediction models in journal and conference abstracts: TRIPOD for abstracts
af: Heus, P, et al.
Udgivet: (2020)

Development and validation of a prediction model with missing predictor data: a practical approach.
af: Vergouwe, Y, et al.
Udgivet: (2010)

Development and validation of a model to predict the risk of exacerbations in chronic obstructive pulmonary disease
af: Bertens LCM, et al.
Udgivet: (2013-10-01)

Transparent reporting of multivariable prediction models developed or validated using clustered data: TRIPOD-Cluster checklist
af: Debray, TPA, et al.
Udgivet: (2023)

External validation of multivariable prediction models : a systematic review of methodological conduct and reporting
af: Collins, G, et al.
Udgivet: (2014)

Transparent reporting of multivariable prediction models developed or validated using clustered data (TRIPOD-Cluster): explanation and elaboration
af: Debray, TPA, et al.
Udgivet: (2023)

Comparative performance of cardiovascular risk prediction models in people living with HIV
af: Irtiza S. Tahir, et al.
Udgivet: (2022-11-01)