Description Usage Arguments Value Author(s) Examples
View source: R/Testing_coefficient_of_mediator.R
Testing coefficient of mediator, namely theta, in the outcome model. The outcome model is the following.
outcome ~ intercept + G*gamma + mediator*theta + error
1 2 | Testing_coefficient_of_mediator(G, mediator, outcome,
outcome_type="continuous", method="score", approxi=TRUE, debug=FALSE)
|
G |
n by p matrix (n rows and p columns). Each row is one individual; each column is one SNP. |
mediator |
a vector length of n. It is the mediator variable. |
outcome |
a vector length of n. It is the outcome variable. |
outcome_type |
Type of the outcome variable. For now, this package only deals with continuous outcome. Default is "continuous". |
method |
The method of testing coefficient of mediator in the outcome model. The score test is used. Default is "score". |
approxi |
a boolean value. This is an indicator whether the approximation of the score statistic is applied to save computing time. Default is TRUE. |
debug |
a boolean value. If TRUE a lot of computing details is printed; otherwise the function is completely silent. Default is FALSE. |
P value for testing the coefficient of mediator in the outcome model.
Wujuan Zhong
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | library(SMUT)
# load the Genotype data included in this R package
data("Genotype_data")
# generate one mediator and one outcome
set.seed(1)
beta=rnorm(ncol(Genotype_data),1,2)
e1 = rnorm(nrow(Genotype_data), 0, 1)
mediator = 1 + eigenMapMatMult(Genotype_data,beta) + e1
theta=0.8
gamma=rnorm(ncol(Genotype_data),0.5,2)
e2 = rnorm(nrow(Genotype_data), 0, 1)
outcome = 2 + eigenMapMatMult(Genotype_data,gamma) + theta*mediator + e2
p_value=Testing_coefficient_of_mediator(G=Genotype_data,mediator=mediator,outcome=outcome)
print(p_value)
# Thanks for using our R package SMUT
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