absolute_weighted_corr_fun {CausalGPS}R Documentation

Check Weighted Covariate Balance Using Absolute Approach

Description

Checks covariate balance based on absolute weighted correlations for given data sets.

Usage

absolute_weighted_corr_fun(w, vw, c)

Arguments

w

A vector of observed continuous exposure variable.

vw

A vector of weights.

c

A data.table of observed covariates variable.

Value

The function returns a list saved the measure related to covariate balance absolute_corr: the absolute correlations for each pre-exposure covairates; mean_absolute_corr: the average absolute correlations for all pre-exposure covairates.

Examples

set.seed(639)
n <- 100
mydata <- generate_syn_data(sample_size=100)
year <- sample(x=c("2001","2002","2003","2004","2005"),size = n, replace = TRUE)
region <- sample(x=c("North", "South", "East", "West"),size = n, replace = TRUE)
mydata$year <- as.factor(year)
mydata$region <- as.factor(region)
mydata$cf5 <- as.factor(mydata$cf5)
data.table::setDT(mydata)
cor_val <- absolute_weighted_corr_fun(mydata[,2],
                                      data.table::data.table(runif(n)),
                                      mydata[, 3:length(mydata)])
print(cor_val$mean_absolute_corr)


[Package CausalGPS version 0.2.7 Index]