Evaluation of data imputation strategies in complex, deeply-phenotyped data sets: the case of the EU-AIMS Longitudinal European Autism Project

Evaluation of data imputation strategies in complex, deeply-phenotyped data sets: the case of the EU-AIMS Longitudinal European Autism Project

Abstract An increasing number of large-scale multi-modal research initiatives has been conducted in the typically developing population, e.g. Dev. Cogn. Neur. 32:43-54, 2018; PLoS Med. 12(3):e1001779, 2015; Elam and Van Essen, Enc. Comp. Neur., 2013, as well as in psychiatric cohorts, e.g. Trans. Ps...

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Bibliographic Details
Main Authors: A. Llera, M. Brammer, B. Oakley, J. Tillmann, M. Zabihi, J. S. Amelink, T. Mei, T. Charman, C. Ecker, F. Dell’Acqua, T. Banaschewski, C. Moessnang, S. Baron-Cohen, R. Holt, S. Durston, D. Murphy, E. Loth, J. K. Buitelaar, D. L. Floris, C. F. Beckmann
Format: Article
Language:English
Published: BMC 2022-08-01
Series:BMC Medical Research Methodology
Subjects:
Imputation
Clinical data
Multivariate
Machine learning
Online Access:https://doi.org/10.1186/s12874-022-01656-z

Internet

https://doi.org/10.1186/s12874-022-01656-z

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