Software application profile: tpc and micd-R packages for causal discovery with incomplete cohort data.
Int J Epidemiol
; 53(5)2024 Aug 14.
Article
em En
| MEDLINE
| ID: mdl-39186942
ABSTRACT
MOTIVATION The Peter Clark (PC) algorithm is a popular causal discovery method to learn causal graphs in a data-driven way. Until recently, existing PC algorithm implementations in R had important limitations regarding missing values, temporal structure or mixed measurement scales (categorical/continuous), which are all common features of cohort data. The new R packages presented here, micd and tpc, fill these gaps. IMPLEMENTATION micd and tpc packages are R packages. GENERAL FEATURES The micd package provides add-on functionality for dealing with missing values to the existing pcalg R package, including methods for multiple imputations relying on the Missing At Random assumption. Also, micd allows for mixed measurement scales assuming conditional Gaussianity. The tpc package efficiently exploits temporal information in a way that results in a more informative output that is less prone to statistical errors. AVAILABILITY:
The tpc and micd packages are freely available on the Comprehensive R Archive Network (CRAN). Their source code is also available on GitHub (https//github.com/bips-hb/micd; https//github.com/bips-hb/tpc).Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
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Software
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Causalidade
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article