absolute_corr_fun {CausalGPS} | R Documentation |
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)
[Package CausalGPS version 0.5.0 Index]