Monte Carlo Method for Indirect Effect in a Standardized Simple Mediation Model Using the Wishart Distribution (Sampling Distribution)
Source:R/mc.R
mc.wishart.RdMonte Carlo Method for Indirect Effect in a Standardized Simple Mediation Model Using the Wishart Distribution (Sampling Distribution)
mc.wishart(R = 20000L, Sigmahat, n, std = TRUE)
Arguments
| R | Integer. Monte Carlo replications. |
|---|---|
| Sigmahat | Numeric matrix. Estimated covariance matrix. |
| n | Integer. Sample size. |
| std | Logical. Standardize the indirect effect \( \hat{\alpha}^{\prime} \hat{\beta}^{\prime} = \hat{\alpha} \hat{\beta} \frac{\hat{\sigma}_x}{\hat{\sigma}_y}\). |
See also
Other monte carlo method functions:
beta_ols_mc.mvn_pcci_simulation(),
beta_ols_mc.mvn_pcci_task(),
beta_ols_mc.mvn_simulation(),
beta_ols_mc.mvn_task(),
beta_ols_mc.mvn(),
exp_ols_mc.mvn_pcci_simulation(),
exp_ols_mc.mvn_pcci_task(),
exp_ols_mc.mvn_simulation(),
exp_ols_mc.mvn_task(),
exp_ols_mc.mvn(),
mc.mvn(),
mc.t(),
mvn_mar_10_mc.mvn_pcci_simulation(),
mvn_mar_10_mc.mvn_pcci_task(),
mvn_mar_10_mc.mvn_simulation(),
mvn_mar_10_mc.mvn_task(),
mvn_mar_10_mc.mvn(),
mvn_mar_20_mc.mvn_pcci_simulation(),
mvn_mar_20_mc.mvn_pcci_task(),
mvn_mar_20_mc.mvn_simulation(),
mvn_mar_20_mc.mvn_task(),
mvn_mar_20_mc.mvn(),
mvn_mar_30_mc.mvn_pcci_simulation(),
mvn_mar_30_mc.mvn_pcci_task(),
mvn_mar_30_mc.mvn_simulation(),
mvn_mar_30_mc.mvn_task(),
mvn_mar_30_mc.mvn(),
mvn_mcar_10_mc.mvn_pcci_simulation(),
mvn_mcar_10_mc.mvn_pcci_task(),
mvn_mcar_10_mc.mvn_simulation(),
mvn_mcar_10_mc.mvn_task(),
mvn_mcar_10_mc.mvn(),
mvn_mcar_20_mc.mvn_pcci_simulation(),
mvn_mcar_20_mc.mvn_pcci_task(),
mvn_mcar_20_mc.mvn_simulation(),
mvn_mcar_20_mc.mvn_task(),
mvn_mcar_20_mc.mvn(),
mvn_mcar_30_mc.mvn_pcci_simulation(),
mvn_mcar_30_mc.mvn_pcci_task(),
mvn_mcar_30_mc.mvn_simulation(),
mvn_mcar_30_mc.mvn_task(),
mvn_mcar_30_mc.mvn(),
mvn_mnar_10_mc.mvn_pcci_simulation(),
mvn_mnar_10_mc.mvn_pcci_task(),
mvn_mnar_10_mc.mvn_simulation(),
mvn_mnar_10_mc.mvn_task(),
mvn_mnar_10_mc.mvn(),
mvn_mnar_20_mc.mvn_pcci_simulation(),
mvn_mnar_20_mc.mvn_pcci_task(),
mvn_mnar_20_mc.mvn_simulation(),
mvn_mnar_20_mc.mvn_task(),
mvn_mnar_20_mc.mvn(),
mvn_mnar_30_mc.mvn_pcci_simulation(),
mvn_mnar_30_mc.mvn_pcci_task(),
mvn_mnar_30_mc.mvn_simulation(),
mvn_mnar_30_mc.mvn_task(),
mvn_mnar_30_mc.mvn(),
mvn_ols_mc.mvn_pcci_simulation(),
mvn_ols_mc.mvn_pcci_task(),
mvn_ols_mc.mvn_simulation(),
mvn_ols_mc.mvn_task(),
mvn_ols_mc.mvn(),
mvn_sem_mc.mvn_pcci_simulation(),
mvn_sem_mc.mvn_pcci_task(),
mvn_sem_mc.mvn_simulation(),
mvn_sem_mc.mvn_task(),
mvn_sem_mc.mvn(),
mvn_std_mc.mvn.delta_pcci_simulation(),
mvn_std_mc.mvn.delta_pcci_task(),
mvn_std_mc.mvn.delta_simulation(),
mvn_std_mc.mvn.delta_task(),
mvn_std_mc.mvn.delta(),
mvn_std_mc.mvn.sem_pcci_simulation(),
mvn_std_mc.mvn.sem_pcci_task(),
mvn_std_mc.mvn.sem_simulation(),
mvn_std_mc.mvn.sem_task(),
mvn_std_mc.mvn.sem(),
mvn_std_mc.mvn.tb_pcci_simulation(),
mvn_std_mc.mvn.tb_pcci_task(),
mvn_std_mc.mvn.tb_simulation(),
mvn_std_mc.mvn.tb_task(),
mvn_std_mc.mvn.tb(),
mvn_std_mc.wishart_pcci_simulation(),
mvn_std_mc.wishart_pcci_task(),
mvn_std_mc.wishart_simulation(),
mvn_std_mc.wishart_task(),
mvn_std_mc.wishart(),
vm_mod_ols_mc.mvn_pcci_simulation(),
vm_mod_ols_mc.mvn_pcci_task(),
vm_mod_ols_mc.mvn_simulation(),
vm_mod_ols_mc.mvn_task(),
vm_mod_ols_mc.mvn(),
vm_mod_sem_mc.mvn_pcci_simulation(),
vm_mod_sem_mc.mvn_pcci_task(),
vm_mod_sem_mc.mvn_simulation(),
vm_mod_sem_mc.mvn_task(),
vm_mod_sem_mc.mvn(),
vm_sev_ols_mc.mvn_pcci_simulation(),
vm_sev_ols_mc.mvn_pcci_task(),
vm_sev_ols_mc.mvn_simulation(),
vm_sev_ols_mc.mvn_task(),
vm_sev_ols_mc.mvn(),
vm_sev_sem_mc.mvn_pcci_simulation(),
vm_sev_sem_mc.mvn_pcci_task(),
vm_sev_sem_mc.mvn_simulation(),
vm_sev_sem_mc.mvn_task(),
vm_sev_sem_mc.mvn()
Author
Ivan Jacob Agaloos Pesigan
Examples
Sigmahat <- cov(jeksterslabRdatarepo::thirst) n <- dim(jeksterslabRdatarepo::thirst)[1] thetahatstar <- mc.wishart( R = 20000L, Sigmahat = Sigmahat, n = n ) hist(thetahatstar)
