mdes_MADE {POMADE} | R Documentation |
Minimum Detectable Effect Size (MDES) for Meta-Analysis With Dependent Effect Sizes
Description
Compute the minimum detectable effect size in a meta-analysis of dependent effect size estimates, given a specified number of studies, power level, estimation method, and further assumptions about the distribution of studies.
Usage
mdes_MADE(
J,
tau,
omega,
rho,
alpha = 0.05,
target_power = 0.8,
d = 0,
model = "CHE",
var_df = "RVE",
sigma2_dist = NULL,
n_ES_dist = NULL,
iterations = 100,
seed = NULL,
warning = TRUE,
upper = 2,
show_lower = FALSE
)
Arguments
J |
Number of studies. Can be one value or a vector of multiple values. |
tau |
Between-study SD. Can be one value or a vector of multiple values. |
omega |
Within-study SD. Can be one value or a vector of multiple values. |
rho |
Correlation coefficient between effect size estimates from the same study. Can be one value or a vector of multiple values. |
alpha |
Level of statistical significance. Can be one value or a vector of multiple values. Default is 0.05. |
target_power |
Numerical value specifying the target power level. Can be one value or a vector of multiple values. |
d |
Contrast value. Can be one value or a vector of multiple values. Default is 0. |
model |
Assumed working model for dependent effect sizes, either
|
var_df |
Indicates the technique used to obtain the sampling variance
of the average effect size estimate and the degrees of freedom, either
|
sigma2_dist |
Distribution of sampling variance estimates from each study. Can be either a single value, a vector of plausible values, or a function that generates random values. |
n_ES_dist |
Distribution of the number of effect sizes per study. Can be either a single value, a vector of plausible values, or a function that generates random values. |
iterations |
Number of iterations per condition (default is 100). |
seed |
Numerical value for a seed to ensure reproducibility of the iterated power approximations. |
warning |
Logical indicating whether to return a warning when either sigma2_dist or n_ES_dist is based on balanced assumptions. |
upper |
Numerical value containing the upper bound of the interval to be searched for the MDES. |
show_lower |
Logical value indicating whether to report lower bound of
the interval searched for the MDES. Default is |
Value
Returns a tibble
with information about the expectation of the
number of studies, the between-study and within-study variance components,
the sample correlation, the contrast effect, the level of statistical
significance, the target power value(s), the minimum detectable effect
size, the number of iterations, the model to handle dependent effect sizes,
and the methods used to obtain sampling variance estimates as well as the
number effect sizes per study.
Examples
mdes_MADE(
J = 30,
tau = 0.05,
omega = 0.02,
rho = 0.2,
model = "CHE",
var_df = "RVE",
sigma2_dist = 4 / 100,
n_ES_dist = 6,
seed = 10052510
)