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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/powerAnalysisNested.R
\name{findRMSEAsamplesizenested}
\alias{findRMSEAsamplesizenested}
\title{Find sample size given a power in nested model comparison}
\usage{
findRMSEAsamplesizenested(rmsea0A = NULL, rmsea0B = NULL, rmsea1A,
rmsea1B = NULL, dfA, dfB, power = 0.8, alpha = 0.05, group = 1)
}
\arguments{
\item{rmsea0A}{The \eqn{H_0} baseline RMSEA}
\item{rmsea0B}{The \eqn{H_0} alternative RMSEA (trivial misfit)}
\item{rmsea1A}{The \eqn{H_1} baseline RMSEA}
\item{rmsea1B}{The \eqn{H_1} alternative RMSEA (target misfit to be rejected)}
\item{dfA}{degree of freedom of the more-restricted model.}
\item{dfB}{degree of freedom of the less-restricted model.}
\item{power}{The desired statistical power.}
\item{alpha}{The alpha level.}
\item{group}{The number of group in calculating RMSEA.}
}
\description{
Find the sample size that the power in rejection the samples from the
alternative pair of RMSEA is just over the specified power.
}
\examples{
findRMSEAsamplesizenested(rmsea0A = 0, rmsea0B = 0, rmsea1A = 0.06,
rmsea1B = 0.05, dfA = 22, dfB = 20, power = 0.80,
alpha = .05, group = 1)
}
\references{
MacCallum, R. C., Browne, M. W., & Cai, L. (2006). Testing
differences between nested covariance structure models: Power analysis and
null hypotheses. \emph{Psychological Methods, 11}(1), 19--35.
\doi{10.1037/1082-989X.11.1.19}
}
\seealso{
\itemize{
\item \code{\link[=plotRMSEApowernested]{plotRMSEApowernested()}} to plot the statistical power for
nested model comparison based on population RMSEA given the sample size
\item \code{\link[=findRMSEApowernested]{findRMSEApowernested()}} to find the power for a given
sample size in nested model comparison based on population RMSEA
}
}
\author{
Bell Clinton
Pavel Panko (Texas Tech University; \email{pavel.panko@ttu.edu})
Sunthud Pornprasertmanit (\email{psunthud@gmail.com})
}
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