feasible: Feasilibity of a chosen threshold.

In thickmatch: Threshold Matching for Thick Description for Optimal Matching in Observational Studies

Description

The program determines whether it is possible to find at least select_num matched pairs with distance not exceeding eps.

Usage

feasible(z,X,p,caliper,dat,ncontrol=1,exact=NULL,
nearexact=NULL,fine=rep(1,length(z)),penalty=1000,nearexpenalty=100,
rank=FALSE,select_num=0,eps=1000)

Arguments

z	A vector whose ith coordinate is 1 for a treated unit and is 0 for a control.
X	A matrix with length(z) rows giving the covariates. X should be of full column rank.
p	A vector of with length(z)=length(p) giving the variable used to define the caliper. For instance, p might be the propensity score.
caliper	If the treated-minus-control difference (in the scale of sd(p)) in p is < -caliper or > caliper, then penalty is added to the distance.
dat	A data frame with length(z) rows. If the match is feasible, the matched portion of dat is returned with additional columns that define the match.
ncontrol	A positive integer giving the number of controls to be matched to each treated subject. If ncontrol is too large, the match will be infeasible.
exact	If not NULL, then a vector of length(z)=length(p) giving variable that need to be exactly matched.
nearexact	If not NULL, then a vector of length length(z) giving variable that need to be exactly matched.
fine	A vector of with length(z)=length(fine) giving the nominal levels that are to be nearly-finely balanced.
penalty	A numeric penalty imposed for each violation of fine balance.
nearexpenalty	The penalty for a mismatch on nearexact.
rank	If rank=TRUE, a rank-based Mahalanobis distance will be calculated. Otherwise (with default value FALSE), a traditional Mahalanobis distance will be computed.
select_num	A positive number giving the required number of matched pairs with distance not exceeding eps.
eps	The threshold whose feasibility is examined.

Details

If there is a feasible matching with at least select_num matched pairs with distance not exceeding eps, then eps is said to be feasible and 1 is returned. Otherwise, eps is said to be infeasible and 0 is returned.

For details, see Rosenbaum (2017).

You MUST install and load the optmatch package to use feasible.

Value

If the match is infeasible, a warning is issued. Otherwise, a binary indicator of whether there are at least select_num matched pairs with distance not exceeding eps.

A match may be infeasible if ncontrol is too large, or if exact matching for exact is impossible.

References

Rosenbaum, P.R. (2017) Imposing Minimax and Quantile Constraints on Optimal Matching in Observational Studies, Journal of Computational and Graphical Statistics, 26:1, 66-78, DOI: 10.1080/10618600.2016.1152971.

Examples

# To run this example, you must load the optmatch package.
data("nysr")
attach(nysr)
X<-cbind(family.income,family.structure,highest.education.parent.in.household,
         female,race.black,race.hispanic,age.teenager,school.dropout)
detach(nysr)
feasible(z=nysr$intense,X=X,p=nysr$plogit,caliper=0.2,dat=nysr,select_num=10,eps=0.5)

thickmatch documentation built on April 14, 2020, 5:30 p.m.