Maarten van Smeden
Maarten van Smeden
University Medical Center Utrecht
Verified email at - Homepage
Cited by
Cited by
Prediction models for diagnosis and prognosis of covid-19 infection: systematic review and critical appraisal
L Wynants, B Van Calster, MMJ Bonten, GS Collins, TPA Debray, ...
BMJ 369, 2020
Latent class models in diagnostic studies when there is no reference standard—a systematic review
M van Smeden, CA Naaktgeboren, JB Reitsma, KGM Moons, ...
American journal of epidemiology 179 (4), 423-431, 2014
No rationale for 1 variable per 10 events criterion for binary logistic regression analysis
M van Smeden, JAH de Groot, KGM Moons, GS Collins, DG Altman, ...
BMC medical research methodology 16 (1), 163, 2016
Sample size for binary logistic prediction models: beyond events per variable criteria
M van Smeden, KGM Moons, JAH de Groot, GS Collins, DG Altman, ...
Statistical methods in medical research 28 (8), 2455-2474, 2019
Value of composite reference standards in diagnostic research
CA Naaktgeboren, LCM Bertens, M van Smeden, JAH de Groot, ...
BMJ 347, f5605, 2013
Diagnostic test accuracy in childhood pulmonary tuberculosis: a Bayesian latent class analysis
SG Schumacher, M van Smeden, N Dendukuri, L Joseph, MP Nicol, M Pai, ...
American journal of epidemiology 184 (9), 690-700, 2016
Measurement error is often neglected in medical literature: a systematic review
TB Brakenhoff, M Mitroiu, RH Keogh, KGM Moons, RHH Groenwold, ...
Journal of clinical epidemiology 98, 89-97, 2018
Calibration: the Achilles heel of predictive analytics
B Van Calster, DJ McLernon, M van Smeden, L Wynants, EW Steyerberg
BMC medicine 17 (1), 1-7, 2019
Evaluating diagnostic accuracy in the face of multiple reference standards
CA Naaktgeboren, JAH De Groot, M van Smeden, KGM Moons, ...
Annals of internal medicine 159 (3), 195-202, 2013
Calculating the sample size required for developing a clinical prediction model
RD Riley, J Ensor, KIE Snell, FE Harrell, GP Martin, JB Reitsma, ...
BMJ 368, 2020
Bias due to composite reference standards in diagnostic accuracy studies
I Schiller, M van Smeden, A Hadgu, M Libman, JB Reitsma, N Dendukuri
Statistics in Medicine 35 (9), 1454-1470, 2016
Random measurement error: why worry? An example of cardiovascular risk factors
TB Brakenhoff, M van Smeden, FLJ Visseren, RHH Groenwold
PloS one 13 (2), e0192298, 2018
Pragmatic trials and real world evidence: outcome measures in the real world
PM Welsing, KO Rengerink, S Collier, L Eckert, M van Smeden, A Ciaglia, ...
Journal of clinical epidemiology 90, 99-107, 2017
Sample size considerations and predictive performance of multinomial logistic prediction models
VMT de Jong, MJC Eijkemans, B van Calster, D Timmerman, KGM Moons, ...
Statistics in medicine 38 (9), 1601-1619, 2019
Impact of predictor measurement heterogeneity across settings on the performance of prediction models: a measurement error perspective
K Luijken, RHH Groenwold, B Van Calster, EW Steyerberg, ...
Statistics in medicine 38 (18), 3444-3459, 2019
Concerns about composite reference standards in diagnostic research
N Dendukuri, I Schiller, J De Groot, M Libman, K Moons, J Reitsma, ...
BMJ 360, 2018
Validation study of the SCREENIVF: an instrument to screen women or men on risk for emotional maladjustment before the start of a fertility treatment
HDL Ockhuijsen, M van Smeden, A van den Hoogen, J Boivin
Fertility and sterility 107 (6), 1370-1379. e5, 2017
Three myths about risk thresholds for prediction models
L Wynants, M van Smeden, DJ McLernon, D Timmerman, EW Steyerberg, ...
BMC medicine 17 (1), 192, 2019
How variation in predictor measurement affects the discriminative ability and transportability of a prediction model
R Pajouheshnia, M van Smeden, LM Peelen, RHH Groenwold
Journal of clinical epidemiology 105, 136-141, 2019
Reflection on modern methods: five myths about measurement error in epidemiological research
M van Smeden, TL Lash, RHH Groenwold
International Journal of Epidemiology 49 (1), 338-347, 2020
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