confint.semmcci {semmcci}

Monte Carlo Confidence Intervals for the Parameter Estimates

Description

Monte Carlo Confidence Intervals for the Parameter Estimates

Usage

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

Arguments

object

Object of class semmcci.

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 arguments.

Value

Returns a matrix of confidence intervals.

Author(s)

Ivan Jacob Agaloos Pesigan

Examples

library(semmcci)
library(lavaan)

# Data ---------------------------------------------------------------------
data("Tal.Or", package = "psych")
df <- mice::ampute(Tal.Or)$amp

# Monte Carlo --------------------------------------------------------------
## Fit Model in lavaan -----------------------------------------------------
model <- "
  reaction ~ cp * cond + b * pmi
  pmi ~ a * cond
  cond ~~ cond
  indirect := a * b
  direct := cp
  total := cp + (a * b)
"
fit <- sem(data = df, model = model, missing = "fiml")

## MC() --------------------------------------------------------------------
unstd <- MC(
  fit,
  R = 5L # use a large value e.g., 20000L for actual research
)

## Standardized Monte Carlo ------------------------------------------------
std <- MCStd(unstd)
confint(unstd)
confint(std)

# Monte Carlo (Multiple Imputation) ----------------------------------------
## Multiple Imputation -----------------------------------------------------
mi <- mice::mice(
  data = df,
  print = FALSE,
  m = 5L, # use a large value e.g., 100L for actual research,
  seed = 42
)

## Fit Model in lavaan -----------------------------------------------------
fit <- sem(data = df, model = model) # use default listwise deletion

## MCMI() ------------------------------------------------------------------
unstd <- MCMI(
  fit,
  mi = mi,
  R = 5L # use a large value e.g., 20000L for actual research
)

## Standardized Monte Carlo ------------------------------------------------
std <- MCStd(unstd)
confint(unstd)
confint(std)