A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis.
about
Individual participant data meta-analysis for a binary outcome: one-stage or two-stage?Prediction models for the risk of postoperative nausea and vomitingDeveloping and validating risk prediction models in an individual participant data meta-analysisIndividual Participant Data (IPD) Meta-analyses of Randomised Controlled Trials: Guidance on Their UseExternal validation of multivariable prediction models: a systematic review of methodological conduct and reportingConcordance measures in shared frailty models: application to clustered data in cancer prognosis.Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE.Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies.Incorporation of individual-patient data in network meta-analysis for multiple continuous endpoints, with application to diabetes treatment.Multivariate meta-analysis using individual participant data.Individual participant data (IPD) meta-analyses of diagnostic and prognostic modeling studies: guidance on their use.Meta-STEPP: subpopulation treatment effect pattern plot for individual patient data meta-analysis.Does ignoring clustering in multicenter data influence the performance of prediction models? A simulation study.Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ.Systematic review of prognostic models for recurrent venous thromboembolism (VTE) post-treatment of first unprovoked VTE.Prediction models for cardiovascular disease risk in the general population: systematic review.Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model.Neurodevelopmental outcomes after cardiac surgery in infancyExternal validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges.Summarising and validating test accuracy results across multiple studies for use in clinical practiceMultivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurementDiagnostic models of the pre-test probability of stable coronary artery disease: A systematic review.Risk prediction models for postoperative delirium: a systematic review and meta-analysis.Meta-analytical synthesis of regression coefficients under different categorization scheme of continuous covariates.Measuring the statistical validity of summary meta-analysis and meta-regression results for use in clinical practice.Early Clinical Features in Systemic Lupus Erythematosus: Can They Be Used to Achieve Earlier Diagnosis? A Risk Prediction Model.A review of statistical updating methods for clinical prediction models.Treatment decisions in multiple sclerosis - insights from real-world observational studies.Addressing data privacy in matched studies via virtual pooling.A closed testing procedure to select an appropriate method for updating prediction models.Dynamic prediction models for clustered and interval-censored outcomes: Investigating the intra-couple correlation in the risk of dementia.Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores.Comparative efficacy and tolerability of new-generation antidepressants for major depressive disorder in children and adolescents: protocol of an individual patient data meta-analysis.A multiple-model generalisation of updating clinical prediction models.Predicting Trajectories of Functional Decline in 60- to 70-Year-Old People.Hierarchical imputation of systematically and sporadically missing data: An approximate Bayesian approach using chained equations.Efficient selective screening for heart failure in elderly men and women from the community: A diagnostic individual participant data meta-analysis.Meta-analysis and aggregation of multiple published prediction models.Quantitative fibronectin to help decision-making in women with symptoms of preterm labour (QUIDS) part 1: Individual participant data meta-analysis and health economic analysis.Lifestyle index for mortality prediction using multiple ageing cohorts in the USA, UK and Europe.
P2860
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P2860
A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis.
description
2013 nî lūn-bûn
@nan
2013 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
A framework for developing, im ...... articipant data meta-analysis.
@ast
A framework for developing, im ...... articipant data meta-analysis.
@en
type
label
A framework for developing, im ...... articipant data meta-analysis.
@ast
A framework for developing, im ...... articipant data meta-analysis.
@en
prefLabel
A framework for developing, im ...... articipant data meta-analysis.
@ast
A framework for developing, im ...... articipant data meta-analysis.
@en
P2093
P2860
P356
P1476
A framework for developing, im ...... articipant data meta-analysis.
@en
P2093
Hendrik Koffijberg
Ikhlaaq Ahmed
Karel G M Moons
Richard David Riley
P2860
P304
P356
10.1002/SIM.5732
P407
P577
2013-01-11T00:00:00Z