absolute_corr_fun: Check covariate balance using absolute approach

In CausalGPS: Matching on Generalized Propensity Scores with Continuous Exposures

Check covariate balance using absolute approach

Description

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

Usage

absolute_corr_fun(w, c)

Arguments

w	A vector of observed continuous exposure variable.
c	A data.frame of observed covariates variable.

Value

The function returns a list including:

• absolute_corr: the absolute correlations for each pre-exposure covariates;

• mean_absolute_corr: the average absolute correlations for all pre-exposure covariates.

Examples

set.seed(291)
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_corr_fun(mydata[,2], mydata[, 3:length(mydata)])
print(cor_val$mean_absolute_corr)

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