R/mvn_mcar_30_unstd_fit.sem.R
mvn_mcar_30_fit.sem.RdFit Simple Mediation Model for Data Generated from a Multivariate Normal Distribution with Data Missing Completely at Random - 30% - Structural Equation Modeling
mvn_mcar_30_fit.sem(data, taskid)
| data |
|
|---|---|
| taskid | Numeric. Task ID. |
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_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()
Ivan Jacob Agaloos Pesigan
taskid <- 1 data <- mvn_dat(taskid = taskid) # mvn_mcar_30_fit.sem ------------------------------------------------- mvn_mcar_30_fit.sem(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 2.250000e+02 1.102721e+02 #> sigma2epsilony mux deltam #> 7.332210e+01 1.000000e+02 2.859258e+01 #> deltay taudothat betahat #> 1.445045e+01 1.077838e-01 7.779895e-01 #> alphahat sigma2hatepsilonyhat sigma2hatepsilonmhat #> 7.232284e-01 7.238675e+01 1.055549e+02 #> deltayhat deltamhat muxhat #> 1.133731e+01 2.715891e+01 9.994848e+01 #> sigma2xhat alphahatbetahat sehattaudothat #> 2.374680e+02 5.626642e-01 2.577192e-02 #> sehatbetahat sehatalphahat sehatsigma2hatepsilonyhat #> 2.620038e-02 2.109376e-02 3.238854e+00 #> sehatsigma2hatepsilonmhat sehatdeltayhat sehatdeltamhat #> 4.722921e+00 1.904463e+00 2.133200e+00 #> sehatmuxhat sehatsigma2xhat #> 4.875507e-01 1.062521e+01# mvn_fit.ols for comparison --------------------------------------- mvn_fit.ols(data = data[complete.cases(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 2.250000e+02 1.102721e+02 #> sigma2epsilony mux deltam #> 7.332210e+01 1.000000e+02 2.859258e+01 #> deltay deltayhat taudothat #> 1.445045e+01 1.133731e+01 1.077838e-01 #> betahat deltamhat alphahat #> 7.779895e-01 2.715891e+01 7.232284e-01 #> alphahatbetahat taudothatprime betahatprime #> 5.626642e-01 1.065460e-01 7.564784e-01 #> alphahatprime alphahatprimebetahatprime sigma2xhat #> 7.352522e-01 5.562024e-01 2.377057e+02 #> sigma2hatepsilonmhat sigma2hatepsilonyhat muxhat #> 1.057664e+02 7.260456e+01 9.994848e+01 #> sehatdeltayhat sehattaudothat sehatbetahat #> 1.906372e+00 2.579775e-02 2.622664e-02 #> sehatdeltamhat sehatalphahat sehattaudothatprimetb #> 2.134269e+00 2.110432e-02 2.550149e-02 #> sehatbetahatprimetb sehatalphahatprimetb sehattaudothatprimedelta #> 2.550149e-02 2.145518e-02 2.548081e-02 #> sehatbetahatprimedelta sehatalphahatprimedelta #> 2.195134e-02 1.453491e-02# mvn_mcar_30_fit.sem with missing data ------------------------------- mcar_30 <- mvn_mcar_30_dat(data = data, taskid = taskid) mvn_mcar_30_fit.sem(data = mcar_30, 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 2.250000e+02 1.102721e+02 #> sigma2epsilony mux deltam #> 7.332210e+01 1.000000e+02 2.859258e+01 #> deltay taudothat betahat #> 1.445045e+01 1.081715e-01 7.777576e-01 #> alphahat sigma2hatepsilonyhat sigma2hatepsilonmhat #> 7.137333e-01 7.465121e+01 1.037345e+02 #> deltayhat deltamhat muxhat #> 1.121061e+01 2.813935e+01 9.996847e+01 #> sigma2xhat alphahatbetahat sehattaudothat #> 2.436734e+02 5.551115e-01 3.027865e-02 #> sehatbetahat sehatalphahat sehatsigma2hatepsilonyhat #> 3.053875e-02 2.176343e-02 3.777518e+00 #> sehatsigma2hatepsilonmhat sehatdeltayhat sehatdeltamhat #> 5.065177e+00 2.123635e+00 2.203419e+00 #> sehatmuxhat sehatsigma2xhat #> 5.050156e-01 1.118593e+01