covbalance {approxmatch}  R Documentation 
For a given match, this function evaluates the balance of variables before and after matching. Balance is evaluated using standardized differences.
covbalance(.data, grouplabel, matches, vars, details)
.data 
A data frame or matrix containing the informations on the 
grouplabel 
Argument describing the group structure. See the description in the
documentation of 
matches 
A character matrix describing the strata structure of the design. Standard
use is the output of Each row of the matrix corresponds to a strata and each entry corresponds to
rowname of 
vars 
A character vector of the names of the variables for which balance should be checked. 
details 
Optional argument. This argument can be used to get other details on the

Standardized difference of the covariates between two groups is computed as difference of the means of the variable over the squared root of the average variance of the variable in the groups.
For better understanding of the matching, details
can be used. This
argument can be used to get summaries of the variables before and after matching.
For example, details = c(mean = 'mean', median = 'function(x) quantile(x, probs=.5)')
given the mean and median of the variables. Only functions that give a single
number summary can be used!
Currently, this function cannot be immediately used for a design with different strata sizes. One way to get around would be to fill in the smaller stratum with false units and making all the strata of equal size.
A list consisting of the following elements.
std_diff 
Standardized differences of the specified variables before and after matching for every pair of groups. 
details 
Only if 
See kwaymatching
for usage.
Bikram Karmakar
data(Dodgeram) ## An example strata structure matches = as.matrix(sample(rownames(Dodgeram), 500), ncol = 5) vars = c("AGE", "SEX.2", "IMPACT3.3", "DR_DRINK") details = c('std_diff', 'mean', 'function(x) diff(range(x))', 'function(x) quantile(x, probs = .9)') names(details) < c('std_diff', 'mean', 'range', '90perc') covbalance(.data=Dodgeram, grouplabel=c("NOSAB", "optSAB", "WITHSABS"), matches = matches, vars = vars, details)