Confidence intervals for mediation prameter estimates.

Source: R/08_regmedint_class_user_methods.R

Construct Wald approximate confidence intervals for the quantities of interest.

# S3 method for regmedint
confint(
  object,
  parm = NULL,
  level = 0.95,
  a0 = NULL,
  a1 = NULL,
  m_cde = NULL,
  c_cond = NULL,
  ...
)

Arguments

object

An object of the regmedint class.

parm

For compatibility with generic. Ignored.

level

A numeric vector of length one. Requested confidence level. Defaults to 0.95.

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.

...

For compatibility with generic.

Value

A numeric matrix of the lower limit and upper limit.

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)
confint(regmedint_obj)
#>            lower      upper
#> cde  -0.03560858 1.11775019
#> pnde  0.07637274 0.90148809
#> tnie -0.05439841 0.09087846
#> tnde  0.08280410 0.91420281
#> pnie -0.04485951 0.06219348
#> te    0.09381303 0.92052785
#> pm   -0.13330488 0.22417743
#> attr(,"args")
#> attr(,"args")$a0
#> [1] 0
#> 
#> attr(,"args")$a1
#> [1] 1
#> 
#> attr(,"args")$m_cde
#> [1] 1
#> 
#> attr(,"args")$c_cond
#> [1] 0.5
#> 
## Evaluate at different values
confint(regmedint_obj, m_cde = 0, c_cond = 1)
#>            lower      upper
#> cde  -0.14886090 1.03037403
#> pnde  0.08040695 0.90420550
#> tnie -0.05352857 0.08968272
#> tnde  0.08167823 0.92185214
#> pnie -0.04444765 0.06168388
#> te    0.09463237 0.92613422
#> pm   -0.12941682 0.21904962
#> attr(,"args")
#> attr(,"args")$a0
#> [1] 0
#> 
#> attr(,"args")$a1
#> [1] 1
#> 
#> attr(,"args")$m_cde
#> [1] 0
#> 
#> attr(,"args")$c_cond
#> [1] 1
#> 
## Change confidence level
confint(regmedint_obj, m_cde = 0, c_cond = 1, level = 0.99)
#>            lower      upper
#> cde  -0.33413214 1.21564526
#> pnde -0.04902118 1.03363363
#> tnie -0.07602870 0.11218285
#> tnde -0.05032266 1.05385303
#> pnie -0.06112213 0.07835835
#> te   -0.03600604 1.05677263
#> pm   -0.18416486 0.27379767
#> attr(,"args")
#> attr(,"args")$a0
#> [1] 0
#> 
#> attr(,"args")$a1
#> [1] 1
#> 
#> attr(,"args")$m_cde
#> [1] 0
#> 
#> attr(,"args")$c_cond
#> [1] 1
#>