simulate_MB4.RdSimulates data from a linear mixed effects model, then calculates REML effect size estimator as described in Pustejovsky, Hedges, & Shadish (2014).
simulate_MB4(
iterations,
beta,
rho,
phi,
tau2_ratio,
tau_corr,
p_const,
r_const,
design,
m,
n,
MB = TRUE
)number of independent iterations of the simulation
vector of fixed effect parameters
intra-class correlation parameter
autocorrelation parameter
ratio of trend variance to intercept variance
correlation between case-specific trends and intercepts
vector of constants for calculating numerator of effect size
vector of constants for calculating denominator of effect size
design matrix. If not specified, it will be calculated based on m, n, and MB.
number of cases. Not used if design is specified.
number of measurement occasions. Not used if design is specified.
If true, a multiple baseline design will be used; otherwise, an AB design will be used. Not used if design is specified.
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. doi:10.3102/1076998614547577
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))
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> Warning: nlminb problem, convergence error code = 1
#> message = iteration limit reached without convergence (10)
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> Warning: nlminb problem, convergence error code = 1
#> message = iteration limit reached without convergence (10)
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> Warning: nlminb problem, convergence error code = 1
#> message = iteration limit reached without convergence (10)
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> Warning: nlminb problem, convergence error code = 1
#> message = iteration limit reached without convergence (10)
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> mean var
#> p_beta 0.90837680 0.61101578
#> r_theta 0.72147970 0.29740891
#> delta_AB 1.26398428 1.23516332
#> nu 4.79898794 13.67828487
#> kappa 0.56663420 0.04460662
#> g_AB 1.00608762 0.88375289
#> V_g_AB 1.26455463 0.47705317
#> cnvg_warn 0.00000000 0.00000000
#> sigma_sq 0.26584306 0.04144766
#> phi 0.54834218 0.04810402
#> Tau.id.var(constant) 0.45563664 0.30812460
#> Tau.id.cov(trend,constant) 0.05572171 0.15741017
#> Tau.id.var(trend) 0.52756257 0.07828586
#> RML_coverage1 0.80000000 0.20000000
#> RML_coverage2 1.00000000 0.00000000
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)
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> Warning: nlminb problem, convergence error code = 1
#> message = iteration limit reached without convergence (10)
#> Warning: 'g_REML()' is deprecated and may be removed in a later version of the package. Please use 'g_mlm()' instead.
#> mean var
#> p_beta 1.0192931 0.0535067723
#> r_theta 0.6543429 0.0258966787
#> delta_AB 1.2628930 0.0525602672
#> nu 7.6334267 0.5645641782
#> kappa 0.3737198 0.0019078439
#> g_AB 1.1326221 0.0399182952
#> V_g_AB 0.2814817 0.0008025115
#> cnvg_warn 0.0000000 0.0000000000
#> sigma_sq 0.3761956 0.0491884499
#> phi 0.6218518 0.0364802924
#> Tau.id.var(constant) 0.2781472 0.0691696359
#> Tau.id.cov(trend,constant) 0.1026264 0.0539395567
#> Tau.id.var(trend) 0.4106620 0.0415239349
#> RML_coverage1 1.0000000 0.0000000000
#> RML_coverage2 1.0000000 0.0000000000