cit: Causal Inference Test

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.

Version: 2.3.1
Depends: R (≥ 3.5.0)
Suggests: tinytest
Published: 2021-05-25
Author: Joshua Millstein ORCID iD [aut, cre]
Maintainer: Joshua Millstein <joshua.millstein at usc.edu>
BugReports: https://github.com/USCbiostats/cit/issues
License: Artistic-2.0
URL: https://github.com/USCbiostats/cit
NeedsCompilation: yes
SystemRequirements: gsl (with development libraries libgsl-dev)
Citation: cit citation info
Materials: README NEWS
CRAN checks: cit results

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Reference manual: cit.pdf
Package source: cit_2.3.1.tar.gz
Windows binaries: r-devel: cit_2.3.1.zip, r-devel-UCRT: cit_2.3.1.zip, r-release: cit_2.3.1.zip, r-oldrel: cit_2.3.1.zip
macOS binaries: r-release (arm64): cit_2.3.1.tgz, r-release (x86_64): cit_2.3.1.tgz, r-oldrel: cit_2.3.1.tgz
Old sources: cit archive

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