mlr.variance {MatchLinReg}

Treatment effect variance

Description

Calculating treatment effect variance, resulting from linear regression.

Usage

mlr.variance(tr, Z.i = NULL, sigsq = 1, details = FALSE
  , idx =1:length(tr))

Arguments

tr

Binary treatment indicator vector (1=treatment, 0=control), whose coefficient in the linear regression model is TE.

Z.i

Matrix of adjustment covariates included in linear regression. We must have nrow(Z.i) == length(tr).

sigsq

Variance of data generation noise.

details

Boolean flag, indicating whether intermediate objects used in generating the constrcutor vector must be returned or not (only when no repeated observations).

idx

Index of observations to be used, with possible duplication, e.g. as indexes of matched subset.

Value

A scalar value is returned for TE variance. If details = TRUE and Z.i is not NULL, then the following objects are attached as attributes:

u.i

Vector of length ncol(Z.i), reflecting the mean difference between groups (control - treatment) for each included covariate.

A

Weighted, within-group covariance matrix of included covariates. It is a square matrix of dimension ncol(Z.i).

iA

Inverse of A.

Author(s)

Alireza S. Mahani, Mansour T.A. Sharabiani

References

Link to a draft paper, documenting the supporting mathematical framework, will be provided in the next release.

Examples

data(lalonde)

tr <- lalonde$treat
Z.i <- as.matrix(lalonde[, c("age", "educ", "black"
  , "hispan", "married", "nodegree", "re74", "re75")])

ret <- mlr.variance(tr = tr, Z.i = Z.i)

# comparing with brute-force approach
X.i <- cbind(tr, 1, Z.i)
ret2 <- (solve(t(X.i) %*% X.i))[1, 1]

cat("check 1:", all.equal(ret2, ret), "\n")

# matching with/without replacement
idx <- mlr.match(tr = tr, X = Z.i, caliper = 1.0
  , replace = FALSE)
idx.wr <- mlr.match(tr = tr, X = Z.i, caliper = 1.0
  , replace = TRUE)

ret3 <- mlr.variance(tr = tr, Z.i = Z.i, idx = idx)
cat("variance - matching without replacement:"
  , ret3, "\n")

ret4 <- mlr.variance(tr = tr, Z.i = Z.i, idx = idx.wr)
cat("variance - matching with replacement:"
  , ret4, "\n")