simulate_MB4: Simulate Model MB4 from Pustejovsky, Hedges, & Shadish (2014)

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

Simulate Model MB4 from Pustejovsky, Hedges, & Shadish (2014)

Description

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

Usage

simulate_MB4(
  iterations,
  beta,
  rho,
  phi,
  tau2_ratio,
  tau_corr,
  p_const,
  r_const,
  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
tau2_ratio	ratio of trend variance to intercept variance
tau_corr	correlation between case-specific trends and intercepts
p_const	vector of constants for calculating numerator of effect size
r_const	vector of constants for calculating denominator of effect size
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

simulate_MB4(iterations = 5, beta = c(0,1,0,0), rho = 0.8, phi = 0.5, 
             tau2_ratio = 0.5, tau_corr = 0, 
             p_const = c(0,1,0,7), r_const = c(1,0,1,0,0), 
             design = design_matrix(3, 16, treat_times=c(5,9,13), center = 12))
             
simulate_MB4(iterations = 5, beta = c(0,1,0,0), rho = 0.8, phi = 0.5, 
             tau2_ratio = 0.5, tau_corr = 0, m = 6, n = 8)
             

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