Handling hybrid and missing data in constraint-based causal discovery to study the etiology of ADHD.
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ABSTRACT:
SUBMITTER: Sokolova E
PROVIDER: S-EPMC5479362 | biostudies-literature | 2017
REPOSITORIES: biostudies-literature
Publications
Handling hybrid and missing data in constraint-based causal discovery to study the etiology of ADHD.
Sokolova Elena E von Rhein Daniel D Naaijen Jilly J Groot Perry P Claassen Tom T Buitelaar Jan J Heskes Tom T
International journal of data science and analytics 20161202 2
Causal discovery is an increasingly important method for data analysis in the field of medical research. In this paper, we consider two challenges in causal discovery that occur very often when working with medical data: a mixture of discrete and continuous variables and a substantial amount of missing values. To the best of our knowledge, there are no methods that can handle both challenges at the same time. In this paper, we develop a new method that can handle these challenges based on the as ...[more]
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