homo_IV1: Estimation causal effect under Assumption 6 in Ding et al. (2011)
Description
Estimation causal effect under Assumption 6 in Ding et al. (2011) when the second order moment of the error term is constant.
Usage
homo_IV1(Z, A, M, Y, X)
Arguments
Z
A vector of the randomization variable.
A
A vector of the first mediator: whether a patient receives antidepressant medication.
M
A vector of the second mediator: whether a patient receives mental health therapy.
Y
A vector of the outcome of interest.
X
A matrix of all the covariates.
Value
betabeta coefficients of Z, A, M and AM.
phatproportion of randomization to the treatment group.
residualresiduals of the regression.
sestandard errors of beta coefficients.
zvaluez-vlues of the beta coefficients.
pvaluep-values of the beta coefficients.
CIconfidence intervals of the beta coefficients.
COVcovariance matrix of the beta coefficients.
serrobust version of standard errors of beta coefficients.
zvaluerrobust version of z-vlues of the beta coefficients.
pvaluerrobust version of p-values of the beta coefficients.
CIrrobust version of confidence intervals of the beta coefficients.
COVrrobust version of covariance matrix of the beta coefficients.
Nsample size
GG is defined in Ding et al. (2010).
WW is defined in Ding et al. (2010).
OmegaOmega is is defined in Ding et al. (2010).
Details
For background of the problem, see Ding et al. (2011).
References
Ding, P., Geng, Z. and Zhou, X. H. (2011). Identifying Causal Effect for Multi-Component Intervention Using Instrumental Variable Method: with A Case Study of IMPACT Data. Technical Report.
