dsld (version 0.2.2)

dsldMatchedATE: dsldMatchedATE

Description

Causal inference via matching models. Wrapper for Matching::Match.

Usage

dsldMatchedATE(data,yName,sName,yesSVal,yesYVal=NULL,
   propensFtn=NULL,k=NULL)

Value

Object of class 'Match'. See documentation in the Matching package.

Arguments

data

Data frame.

yName

Name of the response variable column.

sName

Name of the sensitive attribute column. The attribute must be dichotomous.

yesSVal

S value to be considered "yes," to be coded 1 rather than 0.

yesYVal

Y value to be considered "yes," to be coded 1 rather than 0.

propensFtn

Either 'glm' (logistic), or 'knn'.

k

Number of nearest neighbors if propensFtn='knn'.

Author

N. Matloff

Details

This is a dsld wrapper for Matching::Match.

Matched analysis is typically applied to measuring "treatment effects," but is often applied in situations in which the "treatment," S here, is an immutable attribute such as race or gender. The usual issues concerning observational studies apply.

The function dsldMatchedATE finds the estimated mean difference between the matched Y pairs in the treated/nontreated (exposed and non-exposed) groups, with covariates X in data other than the yName and sName columns.

In the propensity model case, we estimate P(S = 1 | X), either by a logistic or k-NN model.

Examples

data(lalonde,package='Matching')
ll <- lalonde
ll$treat <- as.factor(ll$treat)
ll$re74 <- NULL
ll$re75 <- NULL
summary(dsldMatchedATE(ll,'re78','treat','1')) 
summary(dsldMatchedATE(ll,'re78','treat','1',propensFtn='glm'))
summary(dsldMatchedATE(ll,'re78','treat','1',propensFtn='knn',k=15))