twang (version 0.6-1)

ps.summary: Computes balance measures

Description

Computes balance measures (mean differences and KS statistics) for a particular covariate and a set of propensity score weights. This function is not intended to be called directly by the user but is used by other functions in the package.

Usage

ps.summary(x, t, w, get.means = TRUE, get.ks = TRUE, 
           na.action = c("level", "exclude", "lowest")[1], 
           collapse.by.var = FALSE)
ps.summary.f(x, t, w, get.means = TRUE, get.ks = TRUE, 
             na.action = c("level", "exclude", "lowest")[1], 
             collapse.by.var = TRUE)
ps.summary.n(x, t, w, get.means = TRUE, get.ks = TRUE, 
             na.action = c("level", "exclude", "lowest")[1], 
             collapse.by.var = FALSE)

Arguments

x

a vector containing the data for a single covariate

t

a vector of the same length as x with the 0/1 treatment assigniments

w

a vector of the same length as x with the weights

get.means

if TRUE, mean comparisons are computed

get.ks

if TRUE, the KS statistics are computed

na.action

a string indicating the method for handling missing data

collapse.by.var

if TRUE, then statistics computed for factors are collapsed across the levels

Value

• Returns a data frame containing the balance information.
• tx.mn
  The mean of the treatment group
• tx.sd
  The standard deviation of the treatment group
• ct.mn
  The mean of the control group
• ct.sd
  The standard deviation of the control group
• std.eff.sz
  The standardized effect size, (tx.mn-ct.mn)/tx.sd
• stat
  the t-statistic for numeric variables and the chi-square statistic for continuous variables
• p
  the p-value for the test associated with stat
• ks
  the KS statistic
• ks.pval
  the KS p-value computed using the analytic approximation, which does not necessarily work well with a lot of ties
• get.means and get.ks manipulate the inclusion of certain columns in the returned result.

Details

ps.summary dispatches ps.summary.n or ps.summary.f depending on whether x is a numeric vector or a factor.

See Also

bal.stat, ks.stat, es.stat

Examples

treat <- rbinom(100,1,0.5)
w     <- rexp(100)

# categorical data
x.cat <- factor(sample(letters[1:3],size=100,replace=TRUE))
ps.summary.f(x.cat,treat,w)

# numeric data
x.num <- rnorm(100)
ps.summary.f(x.num,treat,w)

# or let ps.summary figure out which to call
ps.summary(x.num,treat,w)