metagear (version 0.6)

random_d: Random generation of Hedges' d effect sizes.

Description

Generates random Hedges' d (1981, 1982) effect sizes and their variances.

Usage

random_d(K, X_t, var_t, N_t, X_c, var_c, N_c, bias_correction = TRUE)

Arguments

K

Number of effect sizes to generate.

X_t

The population mean (mu) of the (t)reatment group.

var_t

The population variance of the treatment group mean.

N_t

The number of samples of the treatment mean. When a non-negative integer, all treatment means will be estimated using the same N. A vector of unequal N's can also be taken; if so, K will be ignored and the number of randomly generated means will equal the length of that vector, and each mean will be based on each N within the vector.

X_c

The population mean (mu) of the (c)ontrol group.

var_c

The population variance of the control group mean.

N_c

The number of samples of the control mean. When a non-negative integer, all control means will be estimated using the same N. A vector of unequal N's can also be taken; if so, K will be ignored and the number of randomly generated means will equal the length of that vector, and each mean will be based on each N within the vector.

bias_correction

When "FALSE", returns Cohen's g effect sizes that are not adjusted using a small-sample correction (J).

Value

A data table with columns of random effect sizes (d) and their variances (var_d).

References

Hedges, L.V. 1981. Distribution theory for Glass's estimator of effect size and related estimators. Journal of Educational Statistics 6: 107-128.

Hedges, L.V. 1982. Estimation of effect size from a series of independent experiments. Psychological Bulletin 92: 490-499.

Examples

# NOT RUN {
   random_d(K = 5, X_t = 25, var_t = 1, N_t = 15, X_c = 10, var_c = 1, N_c = 15)

# }