standardized_differences: Standardized Differences

In dewittpe/pstools: Propensity Score Analysis Tools

Description

Calculate the standardized differences (percentages).

Usage

standardized_differences(x, ...)

## S3 method for class 'pstools_std_diffs'
plot(x, adj_methods = c("adj_IPW",
  "adj_ACE_Exposed", "adj_ACE_Unexposed", "adj_ACE_MostInfo", "adj_ACE_MWP"),
  ...)

Arguments

x	a logistic regression object, or a pstools_dstats object.
...	ignored at this time.
adj_methods	a character vector, names standardized differences adjustment methods to include in the plot.

Value

A list of data.frames each element of the list is for a different weighting method.

Methods (by class)

• pstools_std_diffs: plotting method for pstools_std_diffs objects.

See Also

psweights, dstats

Examples

data(pride)
glmfit <- stats::glm(PCR_RSV ~ SEX + RSVINF + REGION + AGE + ELTATOP + EINZ + EXT, 
                     data = pride,
                     family = stats::binomial())

std_diff <- standardized_differences(glmfit)

std_diff

# the plot is a ggplot2 object
plot(std_diff)

plot(std_diff, adj_methods = "adj_ACE_MWP") + 
  ggplot2::ggtitle("ACE MWP vs Unadjusted")

dewittpe/pstools documentation built on May 15, 2019, 5:07 a.m.