summary.logis_fe: Result Summaries of Covariate Estimates from a fitted...

In pprof: Modeling, Standardization and Testing for Provider Profiling

Result Summaries of Covariate Estimates from a fitted logis_fe object

Description

Provide the summary statistics for the covariate estimates for a fixed effect logistic model.

Usage

## S3 method for class 'logis_fe'
summary(
  object,
  parm,
  level = 0.95,
  test = "wald",
  null = 0,
  alternative = "two.sided",
  ...
)

Arguments

object	a model fitted from logis_fe.
parm	Specifies a subset of covariates for which the result summaries should be output. By default, all covariates are included.
level	the confidence level during the hypothesis test, meaning a significance level of 1 - \text{level}. The default value is 0.95.
test	a character string specifying the type of testing method. The default is "wald". "wald": wald test. "lr": likelihood ratio test. "score": score test.
null	a number defining the null hypothesis for the covariate estimates. The default value is 0.
alternative	a character string specifying the alternative hypothesis when test = "wald", must be one of "two.sided" (default), "greater", or "less".
...	additional arguments that can be passed to the function.

Value

A data frame containing summary statistics for covariate estimates, with the following columns:

Estimate	the estimates of covariate coefficients.
Std.Error	the standard error of the estimate, included only when test = "wald".
Stat	the test statistic.
p value	the p-value for the hypothesis test.
CI.upper	the lower bound of the confidence interval, included only when test = "wald".
CI.lower	the upper bound of the confidence interval, included only when test = "wald".

Examples

data(ExampleDataBinary)
outcome = ExampleDataBinary$Y
covar = ExampleDataBinary$Z
ID = ExampleDataBinary$ID

fit_fe <- logis_fe(Y = outcome, Z = covar, ID = ID, message = FALSE)
summary.wald <- summary(fit_fe, level = 0.95, test = "wald")
summary.wald

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