print.post_jointVIP {jointVIP} | R Documentation |
Obtains a print for post_jointVIP object
Description
Obtains a print for post_jointVIP object
Usage
## S3 method for class 'post_jointVIP'
print(x, ..., smd = "cross-sample", use_abs = TRUE, bias_tol = 0.01)
Arguments
x |
a post_jointVIP object |
... |
not used |
smd |
specify the standardized mean difference is |
use_abs |
TRUE (default) for absolute measures |
bias_tol |
numeric 0.01 (default) any bias above the absolute bias_tol will be printed |
Value
measures used to create the plot of jointVIP
Examples
data <- data.frame(year = rnorm(50, 200, 5),
pop = rnorm(50, 1000, 500),
gdpPercap = runif(50, 100, 1000),
trt = rbinom(50, 1, 0.5),
out = rnorm(50, 1, 0.2))
# random 20 percent of control as pilot data
pilot_sample_num = sample(which(data$trt == 0),
length(which(data$trt == 0)) *
0.2)
pilot_df = data[pilot_sample_num, ]
analysis_df = data[-pilot_sample_num, ]
treatment = "trt"
outcome = "out"
covariates = names(analysis_df)[!names(analysis_df)
%in% c(treatment, outcome)]
new_jointVIP = create_jointVIP(treatment = treatment,
outcome = outcome,
covariates = covariates,
pilot_df = pilot_df,
analysis_df = analysis_df)
## at this step typically you may wish to do matching or weighting
## the results after can be stored as a post_data
## the post_data here is not matched or weighted, only for illustrative purposes
post_data <- data.frame(year = rnorm(50, 200, 5),
pop = rnorm(50, 1000, 500),
gdpPercap = runif(50, 100, 1000),
trt = rbinom(50, 1, 0.5),
out = rnorm(50, 1, 0.2))
post_dat_jointVIP = create_post_jointVIP(new_jointVIP, post_data)
print(post_dat_jointVIP)
[Package jointVIP version 0.1.2 Index]