A likelihood-based hypothesis testing approach is implemented for assessing causal mediation. Described in Millstein, Chen, and Breton (2016), <DOI:10.1093/bioinformatics/btw135>, it could be used to test for mediation of a known causal association between a DNA variant, the 'instrumental variable', and a clinical outcome or phenotype by gene expression or DNA methylation, the potential mediator. Another example would be testing mediation of the effect of a drug on a clinical outcome by the molecular target. The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limited to a single variable but may be a design matrix representing multiple variables.
Package details |
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Author | Joshua Millstein [aut, cre] (<https://orcid.org/0000-0001-7961-8943>) |
Maintainer | Joshua Millstein <joshua.millstein@usc.edu> |
License | Artistic-2.0 |
Version | 2.3.2 |
URL | https://github.com/USCbiostats/cit |
Package repository | View on CRAN |
Installation |
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