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Confidence intervals of parameters

Source: R/confint.R
confint.pmrm_fit.Rd

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.

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.

Details

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

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)
#>           2.5 %    97.5 %
#> arm_2 0.0491933 0.2607419
#> arm_3 0.1190821 0.3252943