powerBLCS: Power analysis for bivariate latent change score models

In RAMpath: Structural Equation Modeling Using the Reticular Action Model (RAM) Notation

Power analysis for bivariate latent change score models

Description

Calculate power for bivariate latent change score models based on Monte Carlo simulation.

Usage

powerBLCS(N=100, T=5, R=1000, betay=0, my0=0, mys=0, varey=1, 
vary0=1, varys=1, vary0ys=0, alpha=0.05, betax=0, mx0=0, 
mxs=0, varex=1, varx0=1, varxs=1, varx0xs=0, varx0y0=0,  
varx0ys=0, vary0xs=0, varxsys=0, gammax=0, gammay=0, ...)

Arguments

N	Sample size, can be a scalar or a vector. For better performance, make sure N is at least two times of T
T	Number of times, occasions or waves of measurements, can be a scalar or a vector
R	Number of replications to run in Monte Carlo simulation. Recommended 1000 or more
betay	Population parameter values
my0	Population parameter values
mys	Population parameter values
varey	Population parameter values
vary0	Population parameter values
varys	Population parameter values
vary0ys	Population parameter values
betax	Population parameter values
mx0	Population parameter values
mxs	Population parameter values
varex	Population parameter values
varx0	Population parameter values
varxs	Population parameter values
varx0xs	Population parameter values
gammax	Population parameter values
gammay	Population parameter values
varx0y0	Population parameter values
varx0ys	Population parameter values
vary0xs	Population parameter values
varxsys	Population parameter values
alpha	Significance level
...	Options can be used for lavaan

Value

A matrix with power for each parameter.

References

Zhang, Z., & Liu, H. (2018). Sample size and measurement occasion planning for latent change score models through Monte Carlo simulation. In E. Ferrer, S. M. Boker, and K. J. Grimm (Eds.), Advances in longitudinal models for multivariate psychology: A festschrift for Jack McArdle (pp. 189-211). New York, NY: Routledge.

Examples

## Not run: 
powerBLCS(R=1000)

## End(Not run)

RAMpath documentation built on Aug. 27, 2023, 5:06 p.m.