R/mvn_mar_10_unstd_fit.sem.R
mvn_mar_10_fit.sem.RdFit Simple Mediation Model for Data Generated from a Multivariate Normal Distribution with Data Missing at Random - 10% - Structural Equation Modeling
mvn_mar_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_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()
Ivan Jacob Agaloos Pesigan
taskid <- 1 data <- mvn_dat(taskid = taskid) # mvn_mar_10_fit.sem ------------------------------------------------- mvn_mar_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 1.054202e-01 7.847851e-01 #> alphahat sigma2hatepsilonyhat sigma2hatepsilonmhat #> 7.230324e-01 7.152982e+01 1.122597e+02 #> deltayhat deltamhat muxhat #> 1.115750e+01 2.775376e+01 1.007887e+02 #> sigma2xhat alphahatbetahat sehattaudothat #> 2.283914e+02 5.674251e-01 2.543501e-02 #> sehatbetahat sehatalphahat sehatsigma2hatepsilonyhat #> 2.525509e-02 2.218142e-02 3.200512e+00 #> sehatsigma2hatepsilonmhat sehatdeltayhat sehatdeltamhat #> 5.022919e+00 1.935866e+00 2.260630e+00 #> sehatmuxhat sehatsigma2xhat #> 4.781422e-01 1.021908e+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 1.115750e+01 1.054202e-01 #> betahat deltamhat alphahat #> 7.847850e-01 2.775376e+01 7.230324e-01 #> alphahatbetahat taudothatprime betahatprime #> 5.674251e-01 1.019787e-01 7.645737e-01 #> alphahatprime alphahatprimebetahatprime sigma2xhat #> 7.179178e-01 5.489011e-01 2.286200e+02 #> sigma2hatepsilonmhat sigma2hatepsilonyhat muxhat #> 1.124847e+02 7.174506e+01 1.007887e+02 #> sehatdeltayhat sehattaudothat sehatbetahat #> 1.937807e+00 2.546051e-02 2.528041e-02 #> sehatdeltamhat sehatalphahat sehattaudothatprimetb #> 2.261762e+00 2.219253e-02 2.462934e-02 #> sehatbetahatprimetb sehatalphahatprimetb sehattaudothatprimedelta #> 2.462934e-02 2.203554e-02 2.461482e-02 #> sehatbetahatprimedelta sehatalphahatprimedelta #> 2.091115e-02 1.533189e-02# mvn_mar_10_fit.sem with missing data ------------------------------- mar_10 <- mvn_mar_10_dat(data = data, taskid = taskid) mvn_mar_10_fit.sem(data = mar_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 1.206817e-01 7.768552e-01 #> alphahat sigma2hatepsilonyhat sigma2hatepsilonmhat #> 7.153599e-01 7.254260e+01 1.131329e+02 #> deltayhat deltamhat muxhat #> 1.054716e+01 2.843263e+01 1.008192e+02 #> sigma2xhat alphahatbetahat sehattaudothat #> 2.303047e+02 5.557311e-01 2.686656e-02 #> sehatbetahat sehatalphahat sehatsigma2hatepsilonyhat #> 2.661260e-02 2.285265e-02 3.364659e+00 #> sehatsigma2hatepsilonmhat sehatdeltayhat sehatdeltamhat #> 5.217272e+00 2.029991e+00 2.321501e+00 #> sehatmuxhat sehatsigma2xhat #> 4.842806e-01 1.045336e+01