R/results_mvn_mcar_pb.mvn_ci.R
results_mvn_mcar_pb.mvn_ci.RdResults: Simple Mediation Model - Multivariate Normal Distribution - Data Missing Completely at Random - Parametric Bootstrap Confidence Intervals using Full Information Maximum Likelihood
results_mvn_mcar_pb.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_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_pb.mvn_ci, package = "jeksterslabRmedsimple") head(results_mvn_mcar_pb.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 reps #> 1 110.2721 73.3221 100 28.59258 14.45045 0.5097591 0.02432106 5000 #> 2 110.2721 73.3221 100 28.59258 14.45045 0.5106129 0.03452267 5000 #> 3 110.2721 73.3221 100 28.59258 14.45045 0.5107630 0.04911674 5000 #> 4 110.2721 73.3221 100 28.59258 14.45045 0.5096472 0.05503753 5000 #> 5 110.2721 73.3221 100 28.59258 14.45045 0.5104204 0.06385578 5000 #> 6 110.2721 73.3221 100 28.59258 14.45045 0.5099510 0.07891614 5000 #> ci_0.05 ci_0.5 ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 1 0.4335995 0.4488441 0.4629224 0.5581780 0.5738174 0.5912646 0 #> 2 0.4039872 0.4250359 0.4446051 0.5797901 0.6024484 0.6277909 0 #> 3 0.3617486 0.3906788 0.4177391 0.6101406 0.6434303 0.6811686 0 #> 4 0.3439136 0.3758553 0.4058401 0.6213835 0.6591963 0.7022413 0 #> 5 0.3198537 0.3562569 0.3906570 0.6407761 0.6854160 0.7364258 0 #> 6 0.2781339 0.3219017 0.3633573 0.6723422 0.7294069 0.7950621 0 #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 shape_99.9 shape_99 #> 1 0 0 0.1576651 0.1249733 0.09525566 1.072554 1.052386 #> 2 0 0 0.2238037 0.1774125 0.13518498 1.101358 1.073903 #> 3 0 0 0.3194200 0.2527515 0.19240156 1.146212 1.105688 #> 4 0 0 0.3583277 0.2833410 0.21554332 1.164716 1.118723 #> 5 0 0 0.4165721 0.3291591 0.25011910 1.189068 1.136318 #> 6 0 0 0.5169281 0.4075052 0.30898490 1.233851 1.168617 #> shape_95 theta_hit_99.9 theta_hit_99 theta_hit_95 theta_miss_99.9 #> 1 1.034173 0.9986 0.9878 0.9396 0.0014 #> 2 1.048439 0.9976 0.9858 0.9438 0.0024 #> 3 1.068776 0.9992 0.9888 0.9386 0.0008 #> 4 1.076930 0.9986 0.9854 0.9442 0.0014 #> 5 1.089093 0.9990 0.9916 0.9454 0.0010 #> 6 1.108658 0.9982 0.9882 0.9436 0.0018 #> theta_miss_99 theta_miss_95 theta power_99.9 power_99 power_95 #> 1 0.0122 0.0604 0.509902 1 1 1 #> 2 0.0142 0.0562 0.509902 1 1 1 #> 3 0.0112 0.0614 0.509902 1 1 1 #> 4 0.0146 0.0558 0.509902 1 1 1 #> 5 0.0084 0.0546 0.509902 1 1 1 #> 6 0.0118 0.0564 0.509902 1 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 1 1 1 0 0 #> 2 0.065 0 1 1 0 0 #> 3 0.065 1 1 1 0 1 #> 4 0.065 1 1 1 0 0 #> 5 0.065 1 1 1 1 1 #> 6 0.065 0 1 1 0 1 #> moderate_95 strict_99.9 strict_99 strict_95 serlin_95 missing std #> 1 0 0 0 0 1 MAR.10 Unstandardized #> 2 1 0 0 0 1 MAR.10 Unstandardized #> 3 0 0 0 0 1 MAR.10 Unstandardized #> 4 1 0 0 0 1 MAR.10 Unstandardized #> 5 1 1 0 1 1 MAR.10 Unstandardized #> 6 1 0 0 0 1 MAR.10 Unstandardized #> Method n_label alpha_label beta_label taudot_label theta_label #> 1 PBPC.MAR.10 n: 1000 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 2 PBPC.MAR.10 n: 500 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 3 PBPC.MAR.10 n: 250 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 4 PBPC.MAR.10 n: 200 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 5 PBPC.MAR.10 n: 150 α: 0.71 β: 0.71 τ̇: 0.14 0.51(0.71,0.71) #> 6 PBPC.MAR.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 0.0243 0.0345 0.0491 0.055 0.0639 ... #> $ reps : num 5000 5000 5000 5000 5000 5000 5000 5000 5000 5000 ... #> $ ci_0.05 : num 0.434 0.404 0.362 0.344 0.32 ... #> $ ci_0.5 : num 0.449 0.425 0.391 0.376 0.356 ... #> $ ci_2.5 : num 0.463 0.445 0.418 0.406 0.391 ... #> $ ci_97.5 : num 0.558 0.58 0.61 0.621 0.641 ... #> $ ci_99.5 : num 0.574 0.602 0.643 0.659 0.685 ... #> $ ci_99.95 : num 0.591 0.628 0.681 0.702 0.736 ... #> $ 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 0 0 0.0004 0.13 0 ... #> $ len_99.9 : num 0.158 0.224 0.319 0.358 0.417 ... #> $ len_99 : num 0.125 0.177 0.253 0.283 0.329 ... #> $ len_95 : num 0.0953 0.1352 0.1924 0.2155 0.2501 ... #> $ shape_99.9 : num 1.07 1.1 1.15 1.16 1.19 ... #> $ shape_99 : num 1.05 1.07 1.11 1.12 1.14 ... #> $ shape_95 : num 1.03 1.05 1.07 1.08 1.09 ... #> $ theta_hit_99.9 : num 0.999 0.998 0.999 0.999 0.999 ... #> $ theta_hit_99 : num 0.988 0.986 0.989 0.985 0.992 ... #> $ theta_hit_95 : num 0.94 0.944 0.939 0.944 0.945 ... #> $ theta_miss_99.9 : num 0.0014 0.0024 0.0008 0.0014 0.001 0.0018 0.0018 0.0018 0.0016 0.0014 ... #> $ theta_miss_99 : num 0.0122 0.0142 0.0112 0.0146 0.0084 0.0118 0.0136 0.0126 0.0134 0.0128 ... #> $ theta_miss_95 : num 0.0604 0.0562 0.0614 0.0558 0.0546 0.0564 0.0614 0.0588 0.0584 0.0588 ... #> $ 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 1 0 1 1 1 0 0 0 0 1 ... #> $ 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 0 0 0 0 1 0 0 0 0 0 ... #> $ moderate_99 : num 0 0 1 0 1 1 0 0 0 0 ... #> $ moderate_95 : num 0 1 0 1 1 1 0 1 1 1 ... #> $ strict_99.9 : num 0 0 0 0 1 0 0 0 0 0 ... #> $ strict_99 : num 0 0 0 0 0 0 0 0 0 0 ... #> $ strict_95 : num 0 0 0 0 1 0 0 0 0 0 ... #> $ serlin_95 : num 1 1 1 1 1 1 1 1 1 1 ... #> $ missing : chr "MAR.10" "MAR.10" "MAR.10" "MAR.10" ... #> $ std : chr "Unstandardized" "Unstandardized" "Unstandardized" "Unstandardized" ... #> $ Method : chr "PBPC.MAR.10" "PBPC.MAR.10" "PBPC.MAR.10" "PBPC.MAR.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)" ...