R/mvn_mcar_20_unstd_fit.sem.R
mvn_mcar_20_fit.sem.RdFit Simple Mediation Model for Data Generated from a Multivariate Normal Distribution with Data Missing Completely at Random - 20% - Structural Equation Modeling
mvn_mcar_20_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_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_20_fit.sem ------------------------------------------------- mvn_mcar_20_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 1.457013e-01 6.846014e-01 #> alphahat sigma2hatepsilonyhat sigma2hatepsilonmhat #> 7.119018e-01 7.507644e+01 1.036500e+02 #> deltayhat deltamhat muxhat #> 1.634173e+01 2.879764e+01 9.970038e+01 #> sigma2xhat alphahatbetahat sehattaudothat #> 2.130735e+02 4.873690e-01 2.683583e-02 #> sehatbetahat sehatalphahat sehatsigma2hatepsilonyhat #> 2.692678e-02 2.206669e-02 3.359201e+00 #> sehatsigma2hatepsilonmhat sehatdeltayhat sehatdeltamhat #> 4.637688e+00 2.045083e+00 2.223512e+00 #> sehatmuxhat sehatsigma2xhat #> 4.618298e-01 9.533704e+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 1.634173e+01 1.457013e-01 #> betahat deltamhat alphahat #> 6.846014e-01 2.879764e+01 7.119018e-01 #> alphahatbetahat taudothatprime betahatprime #> 4.873690e-01 1.470967e-01 6.888233e-01 #> alphahatprime alphahatprimebetahatprime sigma2xhat #> 7.143146e-01 4.920365e-01 2.132868e+02 #> sigma2hatepsilonmhat sigma2hatepsilonyhat muxhat #> 1.038577e+02 7.530235e+01 9.970038e+01 #> sehatdeltayhat sehattaudothat sehatbetahat #> 2.047133e+00 2.686274e-02 2.695378e-02 #> sehatdeltamhat sehatalphahat sehattaudothatprimetb #> 2.224626e+00 2.207774e-02 2.712000e-02 #> sehatbetahatprimetb sehatalphahatprimetb sehattaudothatprimedelta #> 2.712000e-02 2.215257e-02 2.705551e-02 #> sehatbetahatprimedelta sehatalphahatprimedelta #> 2.385467e-02 1.549516e-02# mvn_mcar_20_fit.sem with missing data ------------------------------- mcar_20 <- mvn_mcar_20_dat(data = data, taskid = taskid) mvn_mcar_20_fit.sem(data = mcar_20, 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 1.409088e-01 6.875678e-01 #> alphahat sigma2hatepsilonyhat sigma2hatepsilonmhat #> 7.051785e-01 7.337474e+01 1.062353e+02 #> deltayhat deltamhat muxhat #> 1.650861e+01 2.952673e+01 9.964210e+01 #> sigma2xhat alphahatbetahat sehattaudothat #> 2.113138e+02 4.848580e-01 2.870914e-02 #> sehatbetahat sehatalphahat sehatsigma2hatepsilonyhat #> 2.815292e-02 2.338341e-02 3.488049e+00 #> sehatsigma2hatepsilonmhat sehatdeltayhat sehatdeltamhat #> 5.043743e+00 2.144665e+00 2.354565e+00 #> sehatmuxhat sehatsigma2xhat #> 4.673127e-01 9.708249e+00