confint.linear_re: Get confidence intervals for provider effects or standardized...

In pprof: Modeling, Standardization and Testing for Provider Profiling

Get confidence intervals for provider effects or standardized measures from a fitted linear_re object

Description

Provide confidence intervals for provider effects or standardized measures from a random effect linear model.

Usage

## S3 method for class 'linear_re'
confint(
  object,
  parm,
  level = 0.95,
  option = "SM",
  stdz = "indirect",
  alternative = "two.sided",
  ...
)

Arguments

object	a model fitted from linear_re.
parm	specify a subset of providers for which confidence intervals are given. By default, all providers are included. The class of parm should match the class of the provider IDs.
level	the confidence level. The default value is 0.95.
option	a character string specifying whether the confidence intervals should be provided for provider effects or standardized measures: "alpha" provider effect. "SM" standardized measures.
stdz	a character string or a vector specifying the standardization method if option includes "SM". See stdz argument in SM_output.linear_re.
alternative	a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater", or "less". Note that "alpha" for argument option only supports "two.sided".
...	additional arguments that can be passed to the function.

Value

A list of data frames containing the confidence intervals based on the values of option and stdz.

CI.alpha	Confidence intervals for provider effects if option includes "alpha".
CI.indirect	Confidence intervals for indirect standardized differences if option includes "SM" and stdz includes "indirect".
CI.direct	Confidence intervals for direct standardized differences if option includes "SM" and stdz includes "direct".

Examples

data(ExampleDataLinear)
outcome <- ExampleDataLinear$Y
ID <- ExampleDataLinear$ID
covar <- ExampleDataLinear$Z
fit_re <- linear_re(Y = outcome, Z = covar, ID = ID)
confint(fit_re)

pprof documentation built on April 12, 2025, 1:33 a.m.