summary.regmedint function

summary method for regmedint object

Summarize the mreg_fit, yreg_fit, and the mediation analysis effect estimates.

## S3 method for class 'regmedint'
summary(
  object,
  a0 = NULL,
  a1 = NULL,
  m_cde = NULL,
  c_cond = NULL,
  args_mreg_fit = list(),
  args_yreg_fit = list(),
  exponentiate = FALSE,
  level = 0.95,
  ...
)

Arguments

• object: An object of the regmedint class.
• a0: A numeric vector of length 1
• a1: A numeric vector of length 1
• m_cde: A numeric vector of length 1 The mediator value at which the controlled direct effect (CDE) conditional on the adjustment covariates is evaluated. If not provided, the default value supplied to the call to regmedint will be used. Only the CDE is affected.
• c_cond: A numeric vector of the same length as cvar. A set of covariate values at which the conditional natural effects are evaluated.
• args_mreg_fit: A named list of argument to be passed to the method for the mreg_fit object.
• args_yreg_fit: A named list of argument to be passed to the method for the mreg_fit object.
• exponentiate: Whether to add exponentiated point and confidence limit estimates. When yreg = "linear", it is ignored.
• level: Confidence level for the confidence intervals.
• ...: For compatibility with the generic. Ignored.

Returns

A summary_regmedint object, which is a list containing the summary objects of the mreg_fit and the yreg_fit as well as the mediation analysis results.

Examples

library(regmedint)
data(vv2015)
regmedint_obj <- regmedint(data = vv2015,
                           ## Variables
                           yvar = "y",
                           avar = "x",
                           mvar = "m",
                           cvar = c("c"),
                           eventvar = "event",
                           ## Values at which effects are evaluated
                           a0 = 0,
                           a1 = 1,
                           m_cde = 1,
                           c_cond = 0.5,
                           ## Model types
                           mreg = "logistic",
                           yreg = "survAFT_weibull",
                           ## Additional specification
                           interaction = TRUE,
                           casecontrol = FALSE)
## Detailed result with summary
summary(regmedint_obj)
## Add exponentiate results for non-linear outcome models
summary(regmedint_obj, exponentiate = TRUE)
## Evaluate at different values
summary(regmedint_obj, m_cde = 0, c_cond = 1)
## Change confidence level
summary(regmedint_obj, m_cde = 0, c_cond = 1, level = 0.99)