R/results_vm_sev_sem_mc.mvn_ci.R
results_vm_sev_sem_mc.mvn_ci.RdResults: Simple Mediation Model - Vale and Maurelli (1983) - Skewness = 3, Kurtosis = 21 - Complete Data - Monte Carlo Method Confidence Intervals with Structural Equation Modeling Parameter Estimates and Robust Standard Errors
results_vm_sev_sem_mc.mvn_ci
A data frame with the following variables
Simulation task identification number.
Sample size.
Monte Carlo replications.
Population slope of path from x to y \(\left( \dot{\tau} \right)\)
Population slope of path from m to y \(\left( \beta \right)\)
Population slope of path from x to m \(\left( \alpha \right)\)
Population indirect effect of x on y through m \(\left( \alpha \beta \right)\)
Population variance of x \(\left( \sigma_{x}^{2} \right)\)
Population error variance of m \(\left( \sigma_{\varepsilon_{m}}^{2} \right)\)
Population error variance of y \(\left( \sigma_{\varepsilon_{y}}^{2} \right)\)
Population mean of x \(\left( \mu_x \right)\).
Population intercept of m \(\left( \delta_m \right)\).
Population intercept of y \(\left( \delta_y \right)\).
Mean of the estimate of the indirect effect \(\left( \hat{\alpha} \hat{\beta} \right)\).
Mean of the estimate of standard error of the indirect effect \(\left( \hat{\alpha} \hat{\beta} \right)\).
Monte Carlo method of bootstrap replications.
Mean of the lower limit confidence interval for the 99.9% confidence interval.
Mean of the lower limit confidence interval for the 99% confidence interval.
Mean of the lower limit confidence interval for the 95% confidence interval.
Mean of the upper limit confidence interval for the 95% confidence interval.
Mean of the upper limit confidence interval for the 99% confidence interval.
Mean of the upper limit confidence interval for the 99.9% confidence interval.
Mean zero hit for the 99.9% confidence interval.
Mean zero hit for the 99% confidence interval.
Mean zero hit for the 95% confidence interval.
Mean confidence interval length for the 99.9% confidence interval.
Mean confidence interval length for the 99% confidence interval.
Mean confidence interval length for the 95% confidence interval.
Mean confidence interval shape for the 99.9% confidence interval.
Mean confidence interval shape for the 99% confidence interval.
Mean confidence interval shape for the 95% confidence interval.
Mean theta hit for the 99.9% confidence interval.
Mean theta hit for the 99% confidence interval.
Mean theta hit for the 95% confidence interval.
Mean theta miss for the 99.9% confidence interval.
Mean theta miss for the 99% confidence interval.
Mean theta miss for the 95% confidence interval.
Population parameter \(\alpha \beta\).
Mean power for the 99.9% confidence interval.
Mean power for the 99% confidence interval.
Mean power for the 95% confidence interval.
Lower limit of the liberal criteria for the 99.9% confidence interval.
Upper limit of the liberal criteria for the 99.9% confidence interval.
Lower limit of the moderate criteria for the 99.9% confidence interval.
Upper limit of the moderate criteria for the 99.9% confidence interval.
Lower limit of the strict criteria for the 99.9% confidence interval.
Upper limit of the strict criteria for the 99.9% confidence interval.
Lower limit of the liberal criteria for the 99% confidence interval.
Upper limit of the liberal criteria for the 99% confidence interval.
Lower limit of the moderate criteria for the 99% confidence interval.
Upper limit of the moderate criteria for the 99% confidence interval.
Lower limit of the strict criteria for the 99% confidence interval.
Upper limit of the strict criteria for the 99% confidence interval.
Lower limit of the liberal criteria for the 95% confidence interval.
Upper limit of the liberal criteria for the 95% confidence interval.
Lower limit of the moderate criteria for the 95% confidence interval.
Upper limit of the moderate criteria for the 95% confidence interval.
Lower limit of the strict criteria for the 95% confidence interval.
Upper limit of the strict criteria for the 95% confidence interval.
Lower limit of the Serlin criteria for the 95% confidence interval.
Upper limit of the Serlin criteria for the 95% confidence interval.
Logical. 1 if miss rate is inside the liberal robustness criteria for 99.9% confidence interval.
Logical. 1 if miss rate is inside the liberal robustness criteria for 99% confidence interval.
Logical. 1 if miss rate is inside the liberal robustness criteria for 95% confidence interval.
Logical. 1 if miss rate is inside the moderate robustness criteria for 99.9% confidence interval.
Logical. 1 if miss rate is inside the moderate robustness criteria for 99% confidence interval.
Logical. 1 if miss rate is inside the moderate robustness criteria for 95% confidence interval.
Logical. 1 if miss rate is inside the strict robustness criteria for 99.9% confidence interval.
Logical. 1 if miss rate is inside the strict robustness criteria for 99% confidence interval.
Logical. 1 if miss rate is inside the strict robustness criteria for 95% confidence interval.
Logical. 1 if miss rate is inside the Serlin robustness criteria for 95% confidence interval.
Type of missingness.
Standardized vs. unstandardize indirect effect.
Method used. Fit in this case.
Sample size labels.
\(\alpha\) labels.
\(\beta\) labels.
\(\dot{\tau}\) labels.
\(\theta\) labels.
The simple mediation model is given by $$ y_i = \delta_y + \dot{\tau} x_i + \beta m_i + \varepsilon_{y_{i}} $$
$$ m_i = \delta_m + \alpha x_i + \varepsilon_{m_{i}} $$
The parameters for the mean structure are $$ \boldsymbol{\theta}_{\text{mean structure}} = \left\{ \mu_x, \delta_m, \delta_y \right\} . $$
The parameters for the covariance structure are $$ \boldsymbol{\theta}_{\text{covariance structure}} = \left\{ \dot{\tau}, \beta, \alpha, \sigma_{x}^{2}, \sigma_{\varepsilon_{m}}^{2}, \sigma_{\varepsilon_{y}}^{2} \right\} . $$
Other results:
results_beta_fit.ols,
results_beta_ols_mc.mvn_ci,
results_exp_fit.ols,
results_exp_ols_mc.mvn_ci,
results_mvn_fit.ols,
results_mvn_fit.sem,
results_mvn_mar_fit.sem,
results_mvn_mar_mc.mvn_ci,
results_mvn_mar_nb.fiml_ci,
results_mvn_mar_pb.mvn_ci,
results_mvn_mcar_fit.sem,
results_mvn_mcar_mc.mvn_ci,
results_mvn_mcar_nb.fiml_ci,
results_mvn_mcar_pb.mvn_ci,
results_mvn_mnar_fit.sem,
results_mvn_mnar_mc.mvn_ci,
results_mvn_mnar_nb.fiml_ci,
results_mvn_nb_ci,
results_mvn_ols_mc.mvn_ci,
results_mvn_pb.mvn_ci,
results_mvn_sem_mc.mvn_ci,
results_vm_mod_fit.ols,
results_vm_mod_fit.sem.mlr,
results_vm_mod_nb_ci,
results_vm_mod_ols_mc.mvn_ci,
results_vm_mod_pb.mvn_ci,
results_vm_mod_sem_mc.mvn_ci,
results_vm_sev_fit.ols,
results_vm_sev_fit.sem.mlr,
results_vm_sev_nb_ci,
results_vm_sev_ols_mc.mvn_ci,
results_vm_sev_pb.mvn_ci
data(results_vm_sev_sem_mc.mvn_ci, package = "jeksterslabRmedsimple") head(results_vm_sev_sem_mc.mvn_ci)#> taskid n simreps taudot beta alpha alphabeta sigma2x #> 1 1 1000 5000 0.1414214 0.7140742 0.7140742 0.509902 225 #> 2 2 500 5000 0.1414214 0.7140742 0.7140742 0.509902 225 #> 3 3 250 5000 0.1414214 0.7140742 0.7140742 0.509902 225 #> 4 4 200 5000 0.1414214 0.7140742 0.7140742 0.509902 225 #> 5 5 150 5000 0.1414214 0.7140742 0.7140742 0.509902 225 #> 6 6 100 5000 0.1414214 0.7140742 0.7140742 0.509902 225 #> sigma2epsilonm sigma2epsilony mux deltam deltay est se #> 1 110.2721 73.3221 100 28.59258 14.45045 0.5136024 0.06090165 #> 2 110.2721 73.3221 100 28.59258 14.45045 0.5146523 0.08170434 #> 3 110.2721 73.3221 100 28.59258 14.45045 0.5197992 0.10620649 #> 4 110.2721 73.3221 100 28.59258 14.45045 0.5188273 0.11489317 #> 5 110.2721 73.3221 100 28.59258 14.45045 0.5154481 0.12630786 #> 6 110.2721 73.3221 100 28.59258 14.45045 0.5195372 0.14347648 #> reps ci_0.05 ci_0.5 ci_2.5 ci_97.5 ci_99.5 ci_99.95 #> 1 20000 0.3302253 0.3662869 0.3990962 0.6376288 0.6797186 0.7294406 #> 2 20000 0.2746268 0.3207271 0.3630146 0.6829018 0.7413027 0.8109018 #> 3 20000 0.2144796 0.2722423 0.3252675 0.7408674 0.8193331 0.9136882 #> 4 20000 0.1909072 0.2525693 0.3093245 0.7588121 0.8446854 0.9483563 #> 5 20000 0.1572239 0.2248431 0.2864678 0.7805325 0.8765144 0.9925692 #> 6 20000 0.1131874 0.1910830 0.2607079 0.8218929 0.9324560 1.0666035 #> zero_hit_99.9 zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 1 0.0000 0.0000 0.0000 0.3992153 0.3134317 0.2385326 #> 2 0.0018 0.0002 0.0000 0.5362750 0.4205755 0.3198872 #> 3 0.0174 0.0028 0.0006 0.6992086 0.5470909 0.4155999 #> 4 0.0302 0.0056 0.0014 0.7574491 0.5921161 0.4494876 #> 5 0.0692 0.0156 0.0022 0.8353453 0.6516713 0.4940647 #> 6 0.1538 0.0488 0.0122 0.9534162 0.7413730 0.5611851 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 theta_hit_95 #> 1 1.174565 1.125391 1.081536 0.9980 0.9886 0.9498 #> 2 1.229912 1.165015 1.106873 0.9978 0.9862 0.9414 #> 3 1.286880 1.206371 1.133646 0.9946 0.9774 0.9184 #> 4 1.306881 1.220036 1.142303 0.9926 0.9732 0.9166 #> 5 1.331389 1.240110 1.155262 0.9894 0.9660 0.9000 #> 6 1.350877 1.257242 1.166785 0.9852 0.9554 0.8872 #> theta_miss_99.9 theta_miss_99 theta_miss_95 theta power_99.9 power_99 #> 1 0.0020 0.0114 0.0502 0.509902 1.0000 1.0000 #> 2 0.0022 0.0138 0.0586 0.509902 0.9982 0.9998 #> 3 0.0054 0.0226 0.0816 0.509902 0.9826 0.9972 #> 4 0.0074 0.0268 0.0834 0.509902 0.9698 0.9944 #> 5 0.0106 0.0340 0.1000 0.509902 0.9308 0.9844 #> 6 0.0148 0.0446 0.1128 0.509902 0.8462 0.9512 #> power_95 liberal_ll_99.9 liberal_ul_99.9 moderate_ll_99.9 moderate_ul_99.9 #> 1 1.0000 5e-04 0.0015 8e-04 0.0012 #> 2 1.0000 5e-04 0.0015 8e-04 0.0012 #> 3 0.9994 5e-04 0.0015 8e-04 0.0012 #> 4 0.9986 5e-04 0.0015 8e-04 0.0012 #> 5 0.9978 5e-04 0.0015 8e-04 0.0012 #> 6 0.9878 5e-04 0.0015 8e-04 0.0012 #> strict_ll_99.9 strict_ul_99.9 liberal_ll_99 liberal_ul_99 moderate_ll_99 #> 1 9e-04 0.0011 0.005 0.015 0.008 #> 2 9e-04 0.0011 0.005 0.015 0.008 #> 3 9e-04 0.0011 0.005 0.015 0.008 #> 4 9e-04 0.0011 0.005 0.015 0.008 #> 5 9e-04 0.0011 0.005 0.015 0.008 #> 6 9e-04 0.0011 0.005 0.015 0.008 #> moderate_ul_99 strict_ll_99 strict_ul_99 liberal_ll_95 liberal_ul_95 #> 1 0.012 0.009 0.011 0.025 0.075 #> 2 0.012 0.009 0.011 0.025 0.075 #> 3 0.012 0.009 0.011 0.025 0.075 #> 4 0.012 0.009 0.011 0.025 0.075 #> 5 0.012 0.009 0.011 0.025 0.075 #> 6 0.012 0.009 0.011 0.025 0.075 #> moderate_ll_95 moderate_ul_95 strict_ll_95 strict_ul_95 serlin_ll_95 #> 1 0.04 0.06 0.045 0.055 0.035 #> 2 0.04 0.06 0.045 0.055 0.035 #> 3 0.04 0.06 0.045 0.055 0.035 #> 4 0.04 0.06 0.045 0.055 0.035 #> 5 0.04 0.06 0.045 0.055 0.035 #> 6 0.04 0.06 0.045 0.055 0.035 #> serlin_ul_95 liberal_99.9 liberal_99 liberal_95 moderate_99.9 moderate_99 #> 1 0.065 0 1 1 0 1 #> 2 0.065 0 1 1 0 0 #> 3 0.065 0 0 0 0 0 #> 4 0.065 0 0 0 0 0 #> 5 0.065 0 0 0 0 0 #> 6 0.065 0 0 0 0 0 #> moderate_95 strict_99.9 strict_99 strict_95 serlin_95 missing std #> 1 1 0 0 1 1 Complete Unstandardized #> 2 1 0 0 0 1 Complete Unstandardized #> 3 0 0 0 0 0 Complete Unstandardized #> 4 0 0 0 0 0 Complete Unstandardized #> 5 0 0 0 0 0 Complete Unstandardized #> 6 0 0 0 0 0 Complete Unstandardized #> Method n_label alpha_label beta_label taudot_label theta_label #> 1 MC n: 1000 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 2 MC n: 500 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 3 MC n: 250 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 4 MC n: 200 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 5 MC n: 150 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 6 MC n: 100 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71)#> 'data.frame': 522 obs. of 79 variables: #> $ taskid : num 1 2 3 4 5 6 7 8 9 10 ... #> $ n : num 1000 500 250 200 150 100 75 50 20 1000 ... #> $ simreps : num 5000 5000 5000 5000 5000 5000 5000 5000 5000 5000 ... #> $ taudot : num 0.141 0.141 0.141 0.141 0.141 ... #> $ beta : num 0.714 0.714 0.714 0.714 0.714 ... #> $ alpha : num 0.714 0.714 0.714 0.714 0.714 ... #> $ alphabeta : num 0.51 0.51 0.51 0.51 0.51 ... #> $ sigma2x : num 225 225 225 225 225 225 225 225 225 225 ... #> $ sigma2epsilonm : num 110 110 110 110 110 ... #> $ sigma2epsilony : num 73.3 73.3 73.3 73.3 73.3 ... #> $ mux : num 100 100 100 100 100 100 100 100 100 100 ... #> $ deltam : num 28.6 28.6 28.6 28.6 28.6 ... #> $ deltay : num 14.5 14.5 14.5 14.5 14.5 ... #> $ est : num 0.514 0.515 0.52 0.519 0.515 ... #> $ se : num 0.0609 0.0817 0.1062 0.1149 0.1263 ... #> $ reps : num 20000 20000 20000 20000 20000 20000 20000 20000 20000 20000 ... #> $ ci_0.05 : num 0.33 0.275 0.214 0.191 0.157 ... #> $ ci_0.5 : num 0.366 0.321 0.272 0.253 0.225 ... #> $ ci_2.5 : num 0.399 0.363 0.325 0.309 0.286 ... #> $ ci_97.5 : num 0.638 0.683 0.741 0.759 0.781 ... #> $ ci_99.5 : num 0.68 0.741 0.819 0.845 0.877 ... #> $ ci_99.95 : num 0.729 0.811 0.914 0.948 0.993 ... #> $ zero_hit_99.9 : num 0 0.0018 0.0174 0.0302 0.0692 ... #> $ zero_hit_99 : num 0 0.0002 0.0028 0.0056 0.0156 ... #> $ zero_hit_95 : num 0 0 0.0006 0.0014 0.0022 0.0122 0.021 0.052 0.207 0 ... #> $ len_99.9 : num 0.399 0.536 0.699 0.757 0.835 ... #> $ len_99 : num 0.313 0.421 0.547 0.592 0.652 ... #> $ len_95 : num 0.239 0.32 0.416 0.449 0.494 ... #> $ shape_99.9 : num 1.17 1.23 1.29 1.31 1.33 ... #> $ shape_99 : num 1.13 1.17 1.21 1.22 1.24 ... #> $ shape_95 : num 1.08 1.11 1.13 1.14 1.16 ... #> $ theta_hit_99.9 : num 0.998 0.998 0.995 0.993 0.989 ... #> $ theta_hit_99 : num 0.989 0.986 0.977 0.973 0.966 ... #> $ theta_hit_95 : num 0.95 0.941 0.918 0.917 0.9 ... #> $ theta_miss_99.9 : num 0.002 0.0022 0.0054 0.0074 0.0106 0.0148 0.0212 0.031 0.0844 0.0022 ... #> $ theta_miss_99 : num 0.0114 0.0138 0.0226 0.0268 0.034 ... #> $ theta_miss_95 : num 0.0502 0.0586 0.0816 0.0834 0.1 ... #> $ theta : num 0.51 0.51 0.51 0.51 0.51 ... #> $ power_99.9 : num 1 0.998 0.983 0.97 0.931 ... #> $ power_99 : num 1 1 0.997 0.994 0.984 ... #> $ power_95 : num 1 1 0.999 0.999 0.998 ... #> $ liberal_ll_99.9 : num 5e-04 5e-04 5e-04 5e-04 5e-04 5e-04 5e-04 5e-04 5e-04 5e-04 ... #> $ liberal_ul_99.9 : num 0.0015 0.0015 0.0015 0.0015 0.0015 0.0015 0.0015 0.0015 0.0015 0.0015 ... #> $ moderate_ll_99.9: num 8e-04 8e-04 8e-04 8e-04 8e-04 8e-04 8e-04 8e-04 8e-04 8e-04 ... #> $ moderate_ul_99.9: num 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 0.0012 ... #> $ strict_ll_99.9 : num 9e-04 9e-04 9e-04 9e-04 9e-04 9e-04 9e-04 9e-04 9e-04 9e-04 ... #> $ strict_ul_99.9 : num 0.0011 0.0011 0.0011 0.0011 0.0011 0.0011 0.0011 0.0011 0.0011 0.0011 ... #> $ liberal_ll_99 : num 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 ... #> $ liberal_ul_99 : num 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 0.015 ... #> $ moderate_ll_99 : num 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 ... #> $ moderate_ul_99 : num 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 ... #> $ strict_ll_99 : num 0.009 0.009 0.009 0.009 0.009 0.009 0.009 0.009 0.009 0.009 ... #> $ strict_ul_99 : num 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 ... #> $ liberal_ll_95 : num 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 ... #> $ liberal_ul_95 : num 0.075 0.075 0.075 0.075 0.075 0.075 0.075 0.075 0.075 0.075 ... #> $ moderate_ll_95 : num 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 ... #> $ moderate_ul_95 : num 0.06 0.06 0.06 0.06 0.06 0.06 0.06 0.06 0.06 0.06 ... #> $ strict_ll_95 : num 0.045 0.045 0.045 0.045 0.045 0.045 0.045 0.045 0.045 0.045 ... #> $ strict_ul_95 : num 0.055 0.055 0.055 0.055 0.055 0.055 0.055 0.055 0.055 0.055 ... #> $ serlin_ll_95 : num 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 ... #> $ serlin_ul_95 : num 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 ... #> $ liberal_99.9 : num 0 0 0 0 0 0 0 0 0 0 ... #> $ liberal_99 : num 1 1 0 0 0 0 0 0 0 1 ... #> $ liberal_95 : num 1 1 0 0 0 0 0 0 0 1 ... #> $ moderate_99.9 : num 0 0 0 0 0 0 0 0 0 0 ... #> $ moderate_99 : num 1 0 0 0 0 0 0 0 0 1 ... #> $ moderate_95 : num 1 1 0 0 0 0 0 0 0 1 ... #> $ strict_99.9 : num 0 0 0 0 0 0 0 0 0 0 ... #> $ strict_99 : num 0 0 0 0 0 0 0 0 0 0 ... #> $ strict_95 : num 1 0 0 0 0 0 0 0 0 1 ... #> $ serlin_95 : num 1 1 0 0 0 0 0 0 0 1 ... #> $ missing : chr "Complete" "Complete" "Complete" "Complete" ... #> $ std : chr "Unstandardized" "Unstandardized" "Unstandardized" "Unstandardized" ... #> $ Method : chr "MC" "MC" "MC" "MC" ... #> $ n_label : Factor w/ 9 levels "n: 20","n: 50",..: 9 8 7 6 5 4 3 2 1 9 ... #> $ alpha_label : Factor w/ 4 levels "α: 0.00","α: 0.38",..: 4 4 4 4 4 4 4 4 4 4 ... #> $ beta_label : Factor w/ 4 levels "β: 0.00","β: 0.38",..: 4 4 4 4 4 4 4 4 4 4 ... #> $ taudot_label : Factor w/ 4 levels "τ̇: 0.00","τ̇: 0.14",..: 2 2 2 2 2 2 2 2 2 1 ... #> $ theta_label : chr "0.51(0.71,0.71)" "0.51(0.71,0.71)" "0.51(0.71,0.71)" "0.51(0.71,0.71)" ...