make_random_effects {EMC2} | R Documentation |
Generate Subject-Level Parameters
Description
Simulates subject-level parameters in the format required by make_data()
.
Usage
make_random_effects(
design,
group_means,
n_subj = NULL,
variance_proportion = 0.2,
covariances = NULL
)
Arguments
design |
A design list. The design as specified by |
group_means |
A numeric vector. The group level means for each parameter, in the same order as |
n_subj |
An integer. The number of subjects to generate parameters for. If |
variance_proportion |
A double. Optional. If |
covariances |
A covariance matrix. Optional. Specify the intended covariance matrix. |
Value
A matrix of subject-level parameters.
Examples
# First create a design
design_DDMaE <- design(data = forstmann,model=DDM,
formula =list(v~0+S,a~E, t0~1, s~1, Z~1, sv~1, SZ~1),
constants=c(s=log(1)))
# Then create a group-level means vector:
group_means =c(v_Sleft=-2,v_Sright=2,a=log(1),a_Eneutral=log(1.5),a_Eaccuracy=log(2),
t0=log(.2),Z=qnorm(.5),sv=log(.5),SZ=qnorm(.5))
# Now we can create subject-level parameters
subj_pars <- make_random_effects(design_DDMaE, group_means, n_subj = 19)
# We can also define a covariance matrix to simulate from
subj_pars <- make_random_effects(design_DDMaE, group_means, n_subj = 19,
covariances = diag(.1, length(group_means)))
# The subject level parameters can be used to generate data
make_data(subj_pars, design_DDMaE, n_trials = 10)
[Package EMC2 version 3.1.1 Index]