View source: R/simulation-functions.R
| compare_RML_HPS | R Documentation | 
Simulates data from a simple linear mixed effects model, then calculates REML and HPS effect size estimators as described in Pustejovsky, Hedges, & Shadish (2014).
compare_RML_HPS(iterations, beta, rho, phi, design, m, n, MB = TRUE)
| 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 | number of cases. Not used if  | 
| n | number of measurement occasions. Not used if  | 
| MB | If true, a multiple baseline design will be used; otherwise, an AB design will be used. Not used if  | 
A matrix reporting the mean and variance of the effect size estimates and various associated statistics.
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")}
compare_RML_HPS(iterations=10, beta = c(0,1,0,0), rho = 0.3, 
                 phi = 0.5, design=design_matrix(m=3,n=8))
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