% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/psychometric_utils.R
\name{compute_sdc}
\alias{compute_sdc}
\title{Compute Smallest Detectable Change (SDC) from SEM}
\usage{
compute_sdc(sem, sem_se)
}
\arguments{
\item{sem}{standard error of measurement}

\item{sem_se}{standard error of the SEM (optional; for propagating uncertainty)}
}
\value{
A data.frame with the SDC, its standard error and 95\% CI.
}
\description{
Compute Smallest Detectable Change (SDC) from SEM
}
\details{
Computes the smallest detectable change (SDC) from the standard error
of measurement:

\deqn{SDC = 1.96 \times \sqrt{2} \times SEM}

The SDC represents the smallest change in scores that can be detected
beyond measurement error with 95\% confidence. If \code{sem_se} is provided,
the uncertainty in SDC is propagated:

\deqn{SDC\_se = 1.96 \times \sqrt{2} \times SEM\_se}
}
\examples{
sem_res <- compute_sem(sd = 10, icc = 0.85, n_sample = 100)
compute_sdc(sem = sem_res$sem, sem_se = sem_res$sem_se)
}
\references{
de Vet, H. C. W., Terwee, C. B., Mokkink, L. B., & Knol, D. L. (2011).
Measurement in Medicine: A Practical Guide. Cambridge University Press.
}
