confint.pmrm_fit: Confidence intervals of parameters

In pmrm: Progression Models for Repeated Measures

Confidence intervals of parameters

Description

Compute confidence intervals of the family of model parameters specified in parm.

Usage

## S3 method for class 'pmrm_fit'
confint(object, parm = NULL, level = 0.95, ...)

Arguments

object	a fitted model object.
parm	a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
level	the confidence level required.
...	additional argument(s) for methods.

Details

See vignette("models", package = "pmrm") for details.

Value

A numeric matrix with one row for each treatment effect parameter (theta) and named columns with the lower and upper bounds of 2-sided confidence intervals on the parameters.

See Also

Other model comparison: AIC.pmrm_fit(), BIC.pmrm_fit(), deviance.pmrm_fit(), glance.pmrm_fit(), logLik.pmrm_fit(), summary.pmrm_fit()

Examples

  set.seed(0L)
  simulation <- pmrm_simulate_decline_proportional(
    visit_times = seq_len(5L) - 1,
    gamma = c(1, 2)
  )
  fit <- pmrm_model_decline_proportional(
    data = simulation,
    outcome = "y",
    time = "t",
    patient = "patient",
    visit = "visit",
    arm = "arm",
    covariates = ~ w_1 + w_2
  )
  confint(fit)

pmrm documentation built on March 12, 2026, 5:07 p.m.