R/mvn_mcar_10_unstd_fit.sem.R
mvn_mcar_10_fit.sem.RdFit Simple Mediation Model for Data Generated from a Multivariate Normal Distribution with Data Missing Completely at Random - 10% - Structural Equation Modeling
mvn_mcar_10_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_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()
Ivan Jacob Agaloos Pesigan
taskid <- 1 data <- mvn_dat(taskid = taskid) # mvn_mcar_10_fit.sem ------------------------------------------------- mvn_mcar_10_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 1.759670e-01 7.256827e-01 #> alphahat sigma2hatepsilonyhat sigma2hatepsilonmhat #> 7.325129e-01 7.505199e+01 1.065197e+02 #> deltayhat deltamhat muxhat #> 9.834517e+00 2.650057e+01 1.007901e+02 #> sigma2xhat alphahatbetahat sehattaudothat #> 2.163309e+02 5.315719e-01 2.693917e-02 #> sehatbetahat sehatalphahat sehatsigma2hatepsilonyhat #> 2.655727e-02 2.220102e-02 3.358106e+00 #> sehatsigma2hatepsilonmhat sehatdeltayhat sehatdeltamhat #> 4.766090e+00 2.024430e+00 2.261343e+00 #> sehatmuxhat sehatsigma2xhat #> 4.653466e-01 9.679455e+00# 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 9.834518e+00 1.759670e-01 #> betahat deltamhat alphahat #> 7.256827e-01 2.650057e+01 7.325129e-01 #> alphahatbetahat taudothatprime betahatprime #> 5.315719e-01 1.672584e-01 6.996879e-01 #> alphahatprime alphahatprimebetahatprime sigma2xhat #> 7.221284e-01 5.052645e-01 2.165475e+02 #> sigma2hatepsilonmhat sigma2hatepsilonyhat muxhat #> 1.067332e+02 7.527782e+01 1.007901e+02 #> sehatdeltayhat sehattaudothat sehatbetahat #> 2.026460e+00 2.696617e-02 2.658389e-02 #> sehatdeltamhat sehatalphahat sehattaudothatprimetb #> 2.262476e+00 2.221214e-02 2.563162e-02 #> sehatbetahatprimetb sehatalphahatprimetb sehattaudothatprimedelta #> 2.563162e-02 2.189725e-02 2.557520e-02 #> sehatbetahatprimedelta sehatalphahatprimedelta #> 2.256368e-02 1.514004e-02# mvn_mcar_10_fit.sem with missing data ------------------------------- mcar_10 <- mvn_mcar_10_dat(data = data, taskid = taskid) mvn_mcar_10_fit.sem(data = mcar_10, 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 1.691824e-01 7.363620e-01 #> alphahat sigma2hatepsilonyhat sigma2hatepsilonmhat #> 7.259400e-01 7.379673e+01 1.063726e+02 #> deltayhat deltamhat muxhat #> 9.411404e+00 2.715649e+01 1.008007e+02 #> sigma2xhat alphahatbetahat sehattaudothat #> 2.190390e+02 5.345547e-01 2.779737e-02 #> sehatbetahat sehatalphahat sehatsigma2hatepsilonyhat #> 2.723279e-02 2.246741e-02 3.405548e+00 #> sehatsigma2hatepsilonmhat sehatdeltayhat sehatdeltamhat #> 4.893302e+00 2.059161e+00 2.288819e+00 #> sehatmuxhat sehatsigma2xhat #> 4.714676e-01 9.908264e+00