1.
Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model
by Snell, Kym I.E
Journal of clinical epidemiology, 2016, Vol.69, p.40-50
2.
Individual participant data meta-analyses should not ignore clustering
by Abo-Zaid, Ghada
Journal of clinical epidemiology, 2013, Vol.66 (8), p.865-873.e4
3.
A new framework to enhance the interpretation of external validation studies of clinical prediction models
by Debray, Thomas P.A
Journal of clinical epidemiology, 2015, Vol.68 (3), p.279-289
4.
Explicit inclusion of treatment in prognostic modeling was recommended in observational and randomized settings
by Groenwold, Rolf H.H
Journal of clinical epidemiology, 2016, Vol.78, p.90-100
5.
Reporting of Bayesian analysis in epidemiologic research should become more transparent
by Rietbergen, Charlotte
Journal of clinical epidemiology, 2017-06, Vol.86, p.51-58.e2
6.
A new framework to enhance the interpretation of external validation studies of clinical prediction models
by Debray, Thomas P.A
Journal of clinical epidemiology, 2015, Vol.68 (3), p.279-289
7.
A new framework to enhance the interpretation of external validation studies of clinical prediction models
by Debray, Thomas P A
Journal of clinical epidemiology, 2015-03-01, Vol.68 (3), p.279
8.
Development and validation of clinical prediction models: Marginal differences between logistic regression, penalized maximum likelihood estimation, and genetic programming
by Janssen, Kristel J.M
Journal of clinical epidemiology, 2012, Vol.65 (4), p.404-412
