R/results_mvn_mcar_mc.mvn_ci.R
results_mvn_mcar_mc.mvn_ci.RdResults: Simple Mediation Model - Multivariate Normal Distribution - Data Missing Completely at Random - Monte Carlo Method Confidence Intervals Structural Equation Modeling with Full Information Maximum Likelihood Parameter Estimates and Standard Errors
results_mvn_mcar_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_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,
results_vm_sev_sem_mc.mvn_ci
data(results_mvn_mcar_mc.mvn_ci, package = "jeksterslabRmedsimple") head(results_mvn_mcar_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 0.5097591 0.02498650 #> 2 110.2721 73.3221 100 28.59258 14.45045 0.5106129 0.03541936 #> 3 110.2721 73.3221 100 28.59258 14.45045 0.5107630 0.05027335 #> 4 110.2721 73.3221 100 28.59258 14.45045 0.5096472 0.05626025 #> 5 110.2721 73.3221 100 28.59258 14.45045 0.5104204 0.06516099 #> 6 110.2721 73.3221 100 28.59258 14.45045 0.5099510 0.08014184 #> reps ci_0.05 ci_0.5 ci_2.5 ci_97.5 ci_99.5 ci_99.95 #> 1 20000 0.4307497 0.4470995 0.4616489 0.5595574 0.5757223 0.5944302 #> 2 20000 0.4003739 0.4227933 0.4429112 0.5816830 0.6051150 0.6324712 #> 3 20000 0.3575065 0.3880324 0.4156471 0.6125526 0.6466977 0.6868483 #> 4 20000 0.3396098 0.3731532 0.4036605 0.6239603 0.6626870 0.7083923 #> 5 20000 0.3158033 0.3537184 0.3883709 0.6435364 0.6889875 0.7429015 #> 6 20000 0.2754087 0.3199916 0.3612928 0.6750009 0.7323046 0.8005822 #> zero_hit_99.9 zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 1 0 0 0 0.1636805 0.1286228 0.09790856 #> 2 0 0 0 0.2320972 0.1823216 0.13877179 #> 3 0 0 0 0.3293419 0.2586653 0.19690549 #> 4 0 0 0 0.3687825 0.2895338 0.22029981 #> 5 0 0 0 0.4270982 0.3352691 0.25516549 #> 6 0 0 0 0.5251735 0.4123131 0.31370802 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 theta_hit_95 #> 1 1.072377 1.052927 1.035191 0.9998 0.9896 0.9478 #> 2 1.106179 1.076324 1.049876 0.9988 0.9882 0.9508 #> 3 1.149974 1.107994 1.070389 0.9992 0.9918 0.9464 #> 4 1.170021 1.121676 1.078856 0.9992 0.9882 0.9492 #> 5 1.195935 1.140182 1.091046 0.9996 0.9926 0.9520 #> 6 1.241433 1.171737 1.110940 0.9990 0.9886 0.9480 #> theta_miss_99.9 theta_miss_99 theta_miss_95 theta power_99.9 power_99 #> 1 0.0002 0.0104 0.0522 0.509902 1 1 #> 2 0.0012 0.0118 0.0492 0.509902 1 1 #> 3 0.0008 0.0082 0.0536 0.509902 1 1 #> 4 0.0008 0.0118 0.0508 0.509902 1 1 #> 5 0.0004 0.0074 0.0480 0.509902 1 1 #> 6 0.0010 0.0114 0.0520 0.509902 1 1 #> power_95 liberal_ll_99.9 liberal_ul_99.9 moderate_ll_99.9 moderate_ul_99.9 #> 1 1 5e-04 0.0015 8e-04 0.0012 #> 2 1 5e-04 0.0015 8e-04 0.0012 #> 3 1 5e-04 0.0015 8e-04 0.0012 #> 4 1 5e-04 0.0015 8e-04 0.0012 #> 5 1 5e-04 0.0015 8e-04 0.0012 #> 6 1 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 1 1 1 1 1 #> 3 0.065 1 1 1 0 1 #> 4 0.065 1 1 1 0 1 #> 5 0.065 0 1 1 0 0 #> 6 0.065 1 1 1 1 1 #> moderate_95 strict_99.9 strict_99 strict_95 serlin_95 missing std #> 1 1 0 1 1 1 MCAR.10 Unstandardized #> 2 1 0 0 1 1 MCAR.10 Unstandardized #> 3 1 0 0 1 1 MCAR.10 Unstandardized #> 4 1 0 0 1 1 MCAR.10 Unstandardized #> 5 1 0 0 1 1 MCAR.10 Unstandardized #> 6 1 1 0 1 1 MCAR.10 Unstandardized #> Method n_label alpha_label beta_label taudot_label theta_label #> 1 MC.MCAR.10 n: 1000 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 2 MC.MCAR.10 n: 500 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 3 MC.MCAR.10 n: 250 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 4 MC.MCAR.10 n: 200 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 5 MC.MCAR.10 n: 150 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 6 MC.MCAR.10 n: 100 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71)#> 'data.frame': 1593 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 0.51 0.511 0.511 0.51 0.51 ... #> $ se : num 0.025 0.0354 0.0503 0.0563 0.0652 ... #> $ reps : num 20000 20000 20000 20000 20000 20000 20000 20000 20000 20000 ... #> $ ci_0.05 : num 0.431 0.4 0.358 0.34 0.316 ... #> $ ci_0.5 : num 0.447 0.423 0.388 0.373 0.354 ... #> $ ci_2.5 : num 0.462 0.443 0.416 0.404 0.388 ... #> $ ci_97.5 : num 0.56 0.582 0.613 0.624 0.644 ... #> $ ci_99.5 : num 0.576 0.605 0.647 0.663 0.689 ... #> $ ci_99.95 : num 0.594 0.632 0.687 0.708 0.743 ... #> $ zero_hit_99.9 : num 0 0 0 0 0 ... #> $ zero_hit_99 : num 0 0 0 0 0 ... #> $ zero_hit_95 : num 0 0 0 0 0 ... #> $ len_99.9 : num 0.164 0.232 0.329 0.369 0.427 ... #> $ len_99 : num 0.129 0.182 0.259 0.29 0.335 ... #> $ len_95 : num 0.0979 0.1388 0.1969 0.2203 0.2552 ... #> $ shape_99.9 : num 1.07 1.11 1.15 1.17 1.2 ... #> $ shape_99 : num 1.05 1.08 1.11 1.12 1.14 ... #> $ shape_95 : num 1.04 1.05 1.07 1.08 1.09 ... #> $ theta_hit_99.9 : num 1 0.999 0.999 0.999 1 ... #> $ theta_hit_99 : num 0.99 0.988 0.992 0.988 0.993 ... #> $ theta_hit_95 : num 0.948 0.951 0.946 0.949 0.952 ... #> $ theta_miss_99.9 : num 0.0002 0.0012 0.0008 0.0008 0.0004 0.001 0.0016 0.002 0.0036 0.001 ... #> $ theta_miss_99 : num 0.0104 0.0118 0.0082 0.0118 0.0074 0.0114 0.0122 0.013 0.0178 0.0094 ... #> $ theta_miss_95 : num 0.0522 0.0492 0.0536 0.0508 0.048 0.052 0.059 0.0568 0.067 0.0504 ... #> $ theta : num 0.51 0.51 0.51 0.51 0.51 ... #> $ power_99.9 : num 1 1 1 1 1 ... #> $ power_99 : num 1 1 1 1 1 ... #> $ power_95 : num 1 1 1 1 1 ... #> $ 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 1 1 1 0 1 0 0 0 1 ... #> $ liberal_99 : num 1 1 1 1 1 1 1 1 0 1 ... #> $ liberal_95 : num 1 1 1 1 1 1 1 1 1 1 ... #> $ moderate_99.9 : num 0 1 0 0 0 1 0 0 0 1 ... #> $ moderate_99 : num 1 1 1 1 0 1 0 0 0 1 ... #> $ moderate_95 : num 1 1 1 1 1 1 1 1 0 1 ... #> $ strict_99.9 : num 0 0 0 0 0 1 0 0 0 1 ... #> $ strict_99 : num 1 0 0 0 0 0 0 0 0 1 ... #> $ strict_95 : num 1 1 1 1 1 1 0 0 0 1 ... #> $ serlin_95 : num 1 1 1 1 1 1 1 1 0 1 ... #> $ missing : chr "MCAR.10" "MCAR.10" "MCAR.10" "MCAR.10" ... #> $ std : chr "Unstandardized" "Unstandardized" "Unstandardized" "Unstandardized" ... #> $ Method : chr "MC.MCAR.10" "MC.MCAR.10" "MC.MCAR.10" "MC.MCAR.10" ... #> $ 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)" ...