in_CI: Indicator Function for Analyzing Coverage

In miceadds: Some Additional Multiple Imputation Functions, Especially for 'mice'

Indicator Function for Analyzing Coverage

Description

Indicator function for analyzing coverage. The output indicates whether a value lies within a computed confidence interval.

Usage

in_CI(est, se, true, level=0.95, df=Inf)

Arguments

est	Vector of estimates
se	Vector of standard errors
true	Vector of true parameters
level	Confidence level
df	Degrees of freedom for t distribution. The default corresponds to the normal distribution.

Value

Logical vector

Examples

#############################################################################
# EXAMPLE 1: Toy example
#############################################################################

#-- simulate estimates and standard errors
set.seed(987)
n <- 10
est <- stats::rnorm( n, sd=1)
se <- stats::runif( n, 0, .7 )
level <- .95
true <- 0

#-- apply coverage function
in_ci <- miceadds::in_CI( est, se, true)
#-- check correctness
cbind( est, se, true, in_ci )

miceadds documentation built on Jan. 7, 2023, 1:09 a.m.