R/results_mvn_mcar_nb.fiml_ci.R
results_mvn_mcar_nb.fiml_ci.RdResults: Simple Mediation Model - Multivariate Normal Distribution - Data Missing Completely at Random - Nonparametric Bootstrap Confidence Intervals using Full Information Maximum Likelihood
results_mvn_mcar_nb.fiml_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_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_nb.fiml_ci, package = "jeksterslabRmedsimple") head(results_mvn_mcar_nb.fiml_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 reps #> 1 110.2721 73.3221 100 28.59258 14.45045 0.5097512 0.0249910 5000 #> 2 110.2721 73.3221 100 28.59258 14.45045 0.5106148 0.0354322 5000 #> 3 110.2721 73.3221 100 28.59258 14.45045 0.5107656 0.0503218 5000 #> 4 110.2721 73.3221 100 28.59258 14.45045 0.5096452 0.0563864 5000 #> 5 110.2721 73.3221 100 28.59258 14.45045 0.5104178 0.0652220 5000 #> 6 110.2721 73.3221 100 28.59258 14.45045 0.5099492 0.0805730 5000 #> ci_0.05 ci_0.5 ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 1 NA 0.4469432 0.4616510 0.5596238 0.5757652 NA NA #> 2 NA 0.4225526 0.4429076 0.5817662 0.6051246 NA NA #> 3 NA 0.3874920 0.4156230 0.6128870 0.6471790 NA NA #> 4 NA 0.3723600 0.4035060 0.6244898 0.6635120 NA NA #> 5 NA 0.3528578 0.3884200 0.6440226 0.6900214 NA NA #> 6 NA 0.3175528 0.3606438 0.6765604 0.7352398 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 shape_99.9 shape_99 #> 1 0 0 NA 0.1288220 0.0979728 NA 1.051808 #> 2 0 0 NA 0.1825720 0.1388586 NA 1.073932 #> 3 0 0 NA 0.2596870 0.1972640 NA 1.107309 #> 4 0 0 NA 0.2911520 0.2209838 NA 1.121578 #> 5 0 0 NA 0.3371636 0.2556026 NA 1.140957 #> 6 0 0 NA 0.4176870 0.3159166 NA 1.173330 #> shape_95 theta_hit_99.9 theta_hit_99 theta_hit_95 theta_miss_99.9 #> 1 1.037315 NA 0.9896 0.9478 NA #> 2 1.051207 NA 0.9874 0.9492 NA #> 3 1.073606 NA 0.9906 0.9450 NA #> 4 1.082298 NA 0.9878 0.9448 NA #> 5 1.095483 NA 0.9922 0.9478 NA #> 6 1.116970 NA 0.9882 0.9450 NA #> theta_miss_99 theta_miss_95 theta power_99.9 power_99 power_95 #> 1 0.0104 0.0522 0.509902 NA 1 1 #> 2 0.0126 0.0508 0.509902 NA 1 1 #> 3 0.0094 0.0550 0.509902 NA 1 1 #> 4 0.0122 0.0552 0.509902 NA 1 1 #> 5 0.0078 0.0522 0.509902 NA 1 1 #> 6 0.0118 0.0550 0.509902 NA 1 1 #> liberal_ll_99.9 liberal_ul_99.9 moderate_ll_99.9 moderate_ul_99.9 #> 1 5e-04 0.0015 8e-04 0.0012 #> 2 5e-04 0.0015 8e-04 0.0012 #> 3 5e-04 0.0015 8e-04 0.0012 #> 4 5e-04 0.0015 8e-04 0.0012 #> 5 5e-04 0.0015 8e-04 0.0012 #> 6 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 NA 1 1 NA 1 #> 2 0.065 NA 1 1 NA 0 #> 3 0.065 NA 1 1 NA 1 #> 4 0.065 NA 1 1 NA 0 #> 5 0.065 NA 1 1 NA 0 #> 6 0.065 NA 1 1 NA 1 #> moderate_95 strict_99.9 strict_99 strict_95 serlin_95 missing std #> 1 1 NA 1 1 1 MCAR.10 Unstandardized #> 2 1 NA 0 1 1 MCAR.10 Unstandardized #> 3 1 NA 1 0 1 MCAR.10 Unstandardized #> 4 1 NA 0 0 1 MCAR.10 Unstandardized #> 5 1 NA 0 1 1 MCAR.10 Unstandardized #> 6 1 NA 0 0 1 MCAR.10 Unstandardized #> Method n_label alpha_label beta_label taudot_label theta_label #> 1 NBPC.FIML.MCAR.10 n: 1000 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 2 NBPC.FIML.MCAR.10 n: 500 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 3 NBPC.FIML.MCAR.10 n: 250 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 4 NBPC.FIML.MCAR.10 n: 200 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 5 NBPC.FIML.MCAR.10 n: 150 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 6 NBPC.FIML.MCAR.10 n: 100 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71)#> 'data.frame': 3186 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 0.0564 0.0652 ... #> $ reps : num 5000 5000 5000 5000 5000 5000 5000 5000 5000 5000 ... #> $ ci_0.05 : num NA NA NA NA NA NA NA NA NA NA ... #> $ ci_0.5 : num 0.447 0.423 0.387 0.372 0.353 ... #> $ 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 0.664 0.69 ... #> $ ci_99.95 : num NA NA NA NA NA NA NA NA NA NA ... #> $ zero_hit_99.9 : num NA NA NA NA NA NA NA NA NA NA ... #> $ zero_hit_99 : num 0 0 0 0 0 ... #> $ zero_hit_95 : num 0 0 0 0 0 ... #> $ len_99.9 : num NA NA NA NA NA NA NA NA NA NA ... #> $ len_99 : num 0.129 0.183 0.26 0.291 0.337 ... #> $ len_95 : num 0.098 0.139 0.197 0.221 0.256 ... #> $ shape_99.9 : num NA NA NA NA NA NA NA NA NA NA ... #> $ shape_99 : num 1.05 1.07 1.11 1.12 1.14 ... #> $ shape_95 : num 1.04 1.05 1.07 1.08 1.1 ... #> $ theta_hit_99.9 : num NA NA NA NA NA NA NA NA NA NA ... #> $ theta_hit_99 : num 0.99 0.987 0.991 0.988 0.992 ... #> $ theta_hit_95 : num 0.948 0.949 0.945 0.945 0.948 ... #> $ theta_miss_99.9 : num NA NA NA NA NA NA NA NA NA NA ... #> $ theta_miss_99 : num 0.0104 0.0126 0.0094 0.0122 0.0078 0.0118 0.014 0.0134 0.0144 0.0086 ... #> $ theta_miss_95 : num 0.0522 0.0508 0.055 0.0552 0.0522 0.055 0.0636 0.0582 0.0596 0.0496 ... #> $ theta : num 0.51 0.51 0.51 0.51 0.51 ... #> $ power_99.9 : num NA NA NA NA NA NA NA NA NA NA ... #> $ 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 NA NA NA NA NA NA NA NA NA NA ... #> $ liberal_99 : num 1 1 1 1 1 1 1 1 1 1 ... #> $ liberal_95 : num 1 1 1 1 1 1 1 1 1 1 ... #> $ moderate_99.9 : num NA NA NA NA NA NA NA NA NA NA ... #> $ moderate_99 : num 1 0 1 0 0 1 0 0 0 1 ... #> $ moderate_95 : num 1 1 1 1 1 1 0 1 1 1 ... #> $ strict_99.9 : num NA NA NA NA NA NA NA NA NA NA ... #> $ strict_99 : num 1 0 1 0 0 0 0 0 0 0 ... #> $ strict_95 : num 1 1 0 0 1 0 0 0 0 1 ... #> $ serlin_95 : num 1 1 1 1 1 1 1 1 1 1 ... #> $ missing : chr "MCAR.10" "MCAR.10" "MCAR.10" "MCAR.10" ... #> $ std : chr "Unstandardized" "Unstandardized" "Unstandardized" "Unstandardized" ... #> $ Method : chr "NBPC.FIML.MCAR.10" "NBPC.FIML.MCAR.10" "NBPC.FIML.MCAR.10" "NBPC.FIML.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)" ...