absolute_weighted_corr_fun: Check Weighted Covariate Balance Using Absolute Approach

In CausalGPS: Matching on Generalized Propensity Scores with Continuous Exposures

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)
cor_val <- absolute_weighted_corr_fun(mydata[,2],
                                      runif(n),
                                      mydata[, 3:length(mydata)])
print(cor_val$mean_absolute_corr)

CausalGPS documentation built on June 22, 2024, 9:31 a.m.