A likelihood-based hypothesis testing approach is implemented for assessing causal mediation. For example, 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.
|Date of publication||2016-11-15 07:16:48|
|Maintainer||Joshua Millstein <firstname.lastname@example.org>|
cit.bp: Causal Inference Test for a Binary Outcome
cit.cp: Causal Inference Test for a Continuous Outcome
cit-package: Causal Inference Test
fdr.cit: Omnibus FDR Values for CIT
fdr.od: Permutation-Based FDR and Confidence Interval
fdr.q.para: Parametric tail-area FDR Values, q-values
fdr.q.perm: Nonparametric permutation-based tail-area FDR Values,...
iuq: Intersection/Union Q-Value
linreg: F Test for Linear Model
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