homo_IV1: Estimation causal effect under Assumption 6 in Ding et al....

In ImpactIV: Identifying Causal Effect for Multi-Component Intervention Using Instrumental Variable Method

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.

Details

For background of the problem, see Ding et al. (2011).

Value

beta	beta coefficients of Z, A, M and AM.
phat	proportion of randomization to the treatment group.
residual	residuals of the regression.
se	standard errors of beta coefficients.
zvalue	z-vlues of the beta coefficients.
pvalue	p-values of the beta coefficients.
CI	confidence intervals of the beta coefficients.
COV	covariance matrix of the beta coefficients.
ser	robust version of standard errors of beta coefficients.
zvaluer	robust version of z-vlues of the beta coefficients.
pvaluer	robust version of p-values of the beta coefficients.
CIr	robust version of confidence intervals of the beta coefficients.
COVr	robust version of covariance matrix of the beta coefficients.
N	sample size
G	G is defined in Ding et al. (2010).
W	W is defined in Ding et al. (2010).
Omega	Omega is is defined in Ding et al. (2010).

Author(s)

Peng Ding <[e-mail]>

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.

Examples

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ImpactIV documentation built on May 1, 2019, 8:04 p.m.