Fit Simple Mediation Model for Data Generated Using the Vale and Maurelli (1983) Approach (Skewness = 3, Kurtosis = 21) - Structural Equation Modeling — vm_sev_std_fit.sem.mlr • jeksterslabRmedsimple

Fit Simple Mediation Model for Data Generated Using the Vale and Maurelli (1983) Approach (Skewness = 3, Kurtosis = 21) - Structural Equation Modeling

vm_sev_std_fit.sem.mlr(data, taskid)

Arguments

data	`n` by 3 matrix or data frame. `data[, 1]` correspond to values for `x`. `data[, 2]` correspond to values for `m`. `data[, 3]` correspond to values for `y`.
taskid	Numeric. Task ID.

See also

Other model fit functions: beta_fit.ols_simulation_summary(), beta_fit.ols_simulation(), beta_fit.ols_task_summary(), beta_fit.ols_task(), beta_fit.ols(), beta_fit.sem.mlr_simulation_summary(), beta_fit.sem.mlr_simulation(), beta_fit.sem.mlr_task_summary(), beta_fit.sem.mlr_task(), beta_fit.sem.mlr(), beta_std_fit.sem.mlr_simulation_summary(), beta_std_fit.sem.mlr_simulation(), beta_std_fit.sem.mlr_task_summary(), beta_std_fit.sem.mlr_task(), beta_std_fit.sem.mlr(), exp_fit.ols_simulation_summary(), exp_fit.ols_simulation(), exp_fit.ols_task_summary(), exp_fit.ols_task(), exp_fit.ols(), exp_fit.sem.mlr_simulation_summary(), exp_fit.sem.mlr_simulation(), exp_fit.sem.mlr_task_summary(), exp_fit.sem.mlr_task(), exp_fit.sem.mlr(), exp_std_fit.sem.mlr_simulation_summary(), exp_std_fit.sem.mlr_simulation(), exp_std_fit.sem.mlr_task_summary(), exp_std_fit.sem.mlr_task(), exp_std_fit.sem.mlr(), fit.cov(), fit.ols(), fit.sem.mlr(), fit.sem(), mvn_fit.ols_simulation_summary(), mvn_fit.ols_simulation(), mvn_fit.ols_task_summary(), mvn_fit.ols_task(), mvn_fit.ols(), mvn_fit.sem_simulation_summary(), mvn_fit.sem_simulation(), mvn_fit.sem_task_summary(), mvn_fit.sem_task(), mvn_fit.sem(), mvn_mar_10_fit.sem_simulation_summary(), mvn_mar_10_fit.sem_simulation(), mvn_mar_10_fit.sem_task_summary(), mvn_mar_10_fit.sem_task(), mvn_mar_10_fit.sem(), mvn_mar_20_fit.sem_simulation_summary(), mvn_mar_20_fit.sem_simulation(), mvn_mar_20_fit.sem_task_summary(), mvn_mar_20_fit.sem_task(), mvn_mar_20_fit.sem(), mvn_mar_30_fit.sem_simulation_summary(), mvn_mar_30_fit.sem_simulation(), mvn_mar_30_fit.sem_task_summary(), mvn_mar_30_fit.sem_task(), mvn_mar_30_fit.sem(), mvn_mcar_10_fit.sem_simulation_summary(), mvn_mcar_10_fit.sem_simulation(), mvn_mcar_10_fit.sem_task_summary(), mvn_mcar_10_fit.sem_task(), mvn_mcar_10_fit.sem(), mvn_mcar_20_fit.sem_simulation_summary(), mvn_mcar_20_fit.sem_simulation(), mvn_mcar_20_fit.sem_task_summary(), mvn_mcar_20_fit.sem_task(), mvn_mcar_20_fit.sem(), mvn_mcar_30_fit.sem_simulation_summary(), mvn_mcar_30_fit.sem_simulation(), mvn_mcar_30_fit.sem_task_summary(), mvn_mcar_30_fit.sem_task(), mvn_mcar_30_fit.sem(), mvn_mnar_10_fit.sem_simulation_summary(), mvn_mnar_10_fit.sem_simulation(), mvn_mnar_10_fit.sem_task_summary(), mvn_mnar_10_fit.sem_task(), mvn_mnar_10_fit.sem(), mvn_mnar_20_fit.sem_simulation_summary(), mvn_mnar_20_fit.sem_simulation(), mvn_mnar_20_fit.sem_task_summary(), mvn_mnar_20_fit.sem_task(), mvn_mnar_20_fit.sem(), mvn_mnar_30_fit.sem_simulation_summary(), mvn_mnar_30_fit.sem_simulation(), mvn_mnar_30_fit.sem_task_summary(), mvn_mnar_30_fit.sem_task(), mvn_mnar_30_fit.sem(), mvn_std_fit.sem_simulation_summary(), mvn_std_fit.sem_simulation(), mvn_std_fit.sem_task_summary(), mvn_std_fit.sem_task(), mvn_std_fit.sem(), vm_mod_fit.ols_simulation_summary(), vm_mod_fit.ols_simulation(), vm_mod_fit.ols_task_summary(), vm_mod_fit.ols_task(), vm_mod_fit.ols(), vm_mod_fit.sem.mlr_simulation_summary(), vm_mod_fit.sem.mlr_simulation(), vm_mod_fit.sem.mlr_task_summary(), vm_mod_fit.sem.mlr_task(), vm_mod_fit.sem.mlr(), vm_mod_std_fit.sem.mlr_simulation_summary(), vm_mod_std_fit.sem.mlr_simulation(), vm_mod_std_fit.sem.mlr_task_summary(), vm_mod_std_fit.sem.mlr_task(), vm_mod_std_fit.sem.mlr(), vm_sev_fit.ols_simulation_summary(), vm_sev_fit.ols_simulation(), vm_sev_fit.ols_task_summary(), vm_sev_fit.ols_task(), vm_sev_fit.ols(), vm_sev_fit.sem.mlr_simulation_summary(), vm_sev_fit.sem.mlr_simulation(), vm_sev_fit.sem.mlr_task_summary(), vm_sev_fit.sem.mlr_task(), vm_sev_fit.sem.mlr(), vm_sev_std_fit.sem.mlr_simulation_summary(), vm_sev_std_fit.sem.mlr_simulation(), vm_sev_std_fit.sem.mlr_task_summary(), vm_sev_std_fit.sem.mlr_task()

Author

Ivan Jacob Agaloos Pesigan

Examples

taskid <- 1
data <- vm_sev_dat(taskid = taskid)
vm_sev_std_fit.sem.mlr(data = data, taskid = taskid)
#>                          taskid                               n 
#>                    1.000000e+00                    1.000000e+03 
#>                            reps                          taudot 
#>                    5.000000e+03                    1.414214e-01 
#>                            beta                           alpha 
#>                    7.140742e-01                    7.140742e-01 
#>                       alphabeta                         sigma2x 
#>                    5.099020e-01                    2.250000e+02 
#>                  sigma2epsilonm                  sigma2epsilony 
#>                    1.102721e+02                    7.332210e+01 
#>                             mux                          deltam 
#>                    1.000000e+02                    2.859258e+01 
#>                          deltay                      lambdaxhat 
#>                    1.445045e+01                    1.428071e+01 
#>                      lambdamhat                      lambdayhat 
#>                    1.546656e+01                    1.585549e+01 
#>                  taudothatprime                    betahatprime 
#>                    1.313515e-01                    7.161703e-01 
#>                   alphahatprime      sigma2hatepsilonylatenthat 
#>                    7.000391e-01                    3.381414e-01 
#>      sigma2hatepsilonmlatenthat                 alphahatbetahat 
#>                    5.099453e-01                    5.013472e-01 
#>                 sehatlambdaxhat                 sehatlambdamhat 
#>                    9.070702e-01                    7.692358e-01 
#>                 sehatlambdayhat             sehattaudothatprime 
#>                    1.184844e+00                    5.038707e-02 
#>               sehatbetahatprime              sehatalphahatprime 
#>                    4.058450e-02                    2.419278e-02 
#> sehatsigma2hatepsilonylatenthat sehatsigma2hatepsilonmlatenthat 
#>                    2.949126e-02                    3.387178e-02