ccmm.sa {ccmm}

Sensitivity analysis

Description

Estimated total indirect effects (TIDE) given correlation coefficients (rho)

Usage

ccmm.sa(y, M, tr, x = NULL, w = NULL, stp = 0.01)

Arguments

y

Vector of continuous outcomes

M

Matrix of compositional data

tr

Vector of continuous or binary treatments

x

Matrix of covariates

w

Vector of weights on samples

stp

Increment of the correlation coefficient

Value

Matrix of rho and TIDE

Author(s)

Michael B. Sohn

Maintainer: Michael B. Sohn <[e-mail]>

References

Sohn, M.B. and Li, H. (2017). Compositional Mediation Analysis for Microbiome Studies (AOAS: In revision)

Examples

# Load test data
data(ccmm_test_data);
outcome <- ccmm_test_data[,1];
treatment <- ccmm_test_data[,2];
mediators <- as.matrix(ccmm_test_data[,3:22]);
covariates <- as.matrix(ccmm_test_data[,23:24]);

rslt.sa <- ccmm.sa(outcome, mediators, treatment, covariates);