Confidence intervals for mediation prameter estimates.
Confidence intervals for mediation prameter estimates.
Construct Wald approximate confidence intervals for the quantities of interest.
## S3 method for class '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.
Returns
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)## Evaluate at different valuesconfint(regmedint_obj, m_cde =0, c_cond =1)## Change confidence levelconfint(regmedint_obj, m_cde =0, c_cond =1, level =0.99)