Fit Standardized Simple Mediation Model for Data with Exponential X - Structural Equation Modeling

Fit Standardized Simple Mediation Model for Data with Exponential X - Structural Equation Modeling

exp_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(), 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(), vm_sev_std_fit.sem.mlr()

Author

Ivan Jacob Agaloos Pesigan

Examples

taskid <- 1
data <- exp_dat(taskid = taskid)
exp_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                    1.000000e+00 
#>                  sigma2epsilonm                  sigma2epsilony 
#>                    4.900980e-01                    3.258760e-01 
#>                             mux                          deltam 
#>                    1.000000e+00                    2.859258e-01 
#>                          deltay                      lambdaxhat 
#>                    1.445045e-01                    1.038000e+00 
#>                      lambdamhat                      lambdayhat 
#>                    1.005978e+00                    1.026915e+00 
#>                  taudothatprime                    betahatprime 
#>                    1.648326e-01                    6.988523e-01 
#>                   alphahatprime      sigma2hatepsilonylatenthat 
#>                    7.166643e-01                    3.193254e-01 
#>      sigma2hatepsilonmlatenthat       alphahatprimebetahatprime 
#>                    4.863922e-01                    5.008425e-01 
#>                 sehatlambdaxhat                 sehatlambdamhat 
#>                    4.627464e-02                    3.014795e-02 
#>                 sehatlambdayhat             sehattaudothatprime 
#>                    2.894926e-02                    2.527859e-02 
#>               sehatbetahatprime              sehatalphahatprime 
#>                    2.217012e-02                    1.980577e-02 
#> sehatsigma2hatepsilonylatenthat sehatsigma2hatepsilonmlatenthat 
#>                    1.985624e-02                    2.838817e-02 
exp_fit.ols(data = data, taskid = taskid)
#>                    taskid                         n                      reps 
#>              1.000000e+00              1.000000e+03              5.000000e+03 
#>                    taudot                      beta                     alpha 
#>              1.414214e-01              7.140742e-01              7.140742e-01 
#>                 alphabeta                   sigma2x            sigma2epsilonm 
#>              5.099020e-01              1.000000e+00              4.900980e-01 
#>            sigma2epsilony                       mux                    deltam 
#>              3.258760e-01              1.000000e+00              2.859258e-01 
#>                    deltay                 deltayhat                 taudothat 
#>              1.445045e-01              1.070574e-01              1.630722e-01 
#>                   betahat                 deltamhat                  alphahat 
#>              7.133971e-01              2.960510e-01              6.945553e-01 
#>           alphahatbetahat            taudothatprime              betahatprime 
#>              4.954937e-01              1.648325e-01              6.988523e-01 
#>             alphahatprime alphahatprimebetahatprime                sigma2xhat 
#>              7.166643e-01              5.008425e-01              1.077445e+00 
#>      sigma2hatepsilonmhat      sigma2hatepsilonyhat                    muxhat 
#>              4.927183e-01              3.374215e-01              1.021066e+00 
#>            sehatdeltayhat            sehattaudothat              sehatbetahat 
#>              2.691453e-02              2.538708e-02              2.619520e-02 
#>            sehatdeltamhat             sehatalphahat     sehattaudothatprimetb 
#>              3.114431e-02              2.139533e-02              2.566113e-02 
#>       sehatbetahatprimetb      sehatalphahatprimetb  sehattaudothatprimedelta 
#>              2.566113e-02              2.207639e-02              2.560461e-02 
#>    sehatbetahatprimedelta   sehatalphahatprimedelta 
#>              2.253930e-02              1.538878e-02