compare_RML_HPS: Run simulation comparing REML and HPS estimates

In scdhlm: Estimating Hierarchical Linear Models for Single-Case Designs

Run simulation comparing REML and HPS estimates

Description

Simulates data from a simple linear mixed effects model, then calculates REML and HPS effect size estimators as described in Pustejovsky, Hedges, & Shadish (2014).

Usage

compare_RML_HPS(iterations, beta, rho, phi, design, m, n, MB = TRUE)

Arguments

iterations	number of independent iterations of the simulation
beta	vector of fixed effect parameters
rho	intra-class correlation parameter
phi	autocorrelation parameter
design	design matrix. If not specified, it will be calculated based on m, n, and MB.
m	number of cases. Not used if design is specified.
n	number of measurement occasions. Not used if design is specified.
MB	If true, a multiple baseline design will be used; otherwise, an AB design will be used. Not used if design is specified.

Value

A matrix reporting the mean and variance of the effect size estimates and various associated statistics.

References

Pustejovsky, J. E., Hedges, L. V., & Shadish, W. R. (2014). Design-comparable effect sizes in multiple baseline designs: A general modeling framework. Journal of Educational and Behavioral Statistics, 39(4), 211-227. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3102/1076998614547577")}

Examples

compare_RML_HPS(iterations=10, beta = c(0,1,0,0), rho = 0.3, 
                 phi = 0.5, design=design_matrix(m=3,n=8))

scdhlm documentation built on March 31, 2023, 10:55 p.m.