qom: Quality of Match In nbpMatching: Functions for Optimal Non-Bipartite Matching

Description

Quality of matches show how well matched pairs differ. For each variable the average distance is generated. Each item in a pair is assigned a group and after several iterations the quantile of these average distances is returned.

Usage

 ```1 2``` ```qom(covariate, matches, iterations = 10000, probs = NA, use.se = FALSE, all.vals = FALSE, seed = 101, ...) ```

Arguments

 `covariate` A data.frame object. `matches` A data.frame or nonbimatch object. Contains information on how to match the covariate data set. `iterations` An integer. Number of iterations to run, defaults to 10,000. `probs` A numeric vector. Probabilities to pass to the quantile function. `use.se` A logical value. Determines if the standard error should be computed. Default value of FALSE. `all.vals` A logical value. Determines if false matches should be included in comparison. Default value of FALSE. `seed` Seed provided for random-number generation. Default value of 101. `...` Additional arguments, not used at the moment.

Details

This fuction is useful for determining the effectiveness of your weights (when generating a distance matrix). Weighting a variable more will lower the average distance, but it could penalize the distance of the other variables. Calculating the standard error requires calling `hdquantile` from Hmisc. The quantiles may be slighly different when using `hdquantile`.

Value

a list object containing elements with quality of match information

 `q` data.frame with quantiles for each covariate `se` data.frame with standard error for each covariate `sd` vector with standard deviate for each covariate

Cole Beck

Examples

 ```1 2 3 4 5 6``` ```df <- data.frame(id=LETTERS[1:25], val1=rnorm(25), val2=rnorm(25)) df.dist <- gendistance(df, idcol=1) df.mdm <- distancematrix(df.dist) df.match <- nonbimatch(df.mdm) qom(df.dist\$cov, df.match) qom(df.dist\$cov, df.match\$matches) ```

nbpMatching documentation built on May 31, 2017, 3:25 a.m.