Nonparametric Bootstrap Estimates with FIML of Indirect Effect in a Simple Mediation Model for Data Generated from a Multivariate Normal Distribution

nbbc.fiml(data, B = 5000L, taskid, mpluspath = "~/.mplus/mplus")

Arguments

data

n by 3 matrix or data frame. data[, 1] correspond to values for x. data[, 2] correspond to values for m. data[, 3] correspond to values for y.

B

Integer. Number of bootstrap samples.

taskid

Numeric. Task ID.

mpluspath

Mplus path.

See also

Other nonparametric functions: beta_nb_bcaci_simulation(), beta_nb_bcaci_task(), beta_nb_bcci_simulation(), beta_nb_bcci_task(), beta_nb_pcci_simulation(), beta_nb_pcci_task(), beta_nb_simulation(), beta_nb_task(), beta_nb(), exp_nb_bcaci_simulation(), exp_nb_bcaci_task(), exp_nb_bcci_simulation(), exp_nb_bcci_task(), exp_nb_pcci_simulation(), exp_nb_pcci_task(), exp_nb_simulation(), exp_nb_task(), exp_nb(), mvn_mar_10_nb.del_bcci_simulation(), mvn_mar_10_nb.del_bcci_task(), mvn_mar_10_nb.del_pcci_simulation(), mvn_mar_10_nb.del_pcci_task(), mvn_mar_10_nb.del_simulation(), mvn_mar_10_nb.del_task(), mvn_mar_10_nb.del(), mvn_mar_10_nb.fiml_bcci_simulation(), mvn_mar_10_nb.fiml_pcci_simulation(), mvn_mar_10_nb_bcci_simulation(), mvn_mar_10_nb_bcci_task(), mvn_mar_10_nb_pcci_simulation(), mvn_mar_10_nb_pcci_task(), mvn_mar_10_nb_simulation(), mvn_mar_10_nb_task(), mvn_mar_10_nbbc.fiml_simulation(), mvn_mar_10_nbbc.fiml_task(), mvn_mar_10_nbpc.fiml_simulation(), mvn_mar_10_nbpc.fiml_task(), mvn_mar_10_nb(), mvn_mar_20_nb.del_bcci_simulation(), mvn_mar_20_nb.del_bcci_task(), mvn_mar_20_nb.del_pcci_simulation(), mvn_mar_20_nb.del_pcci_task(), mvn_mar_20_nb.del_simulation(), mvn_mar_20_nb.del_task(), mvn_mar_20_nb.del(), mvn_mar_20_nb.fiml_bcci_simulation(), mvn_mar_20_nb.fiml_pcci_simulation(), mvn_mar_20_nb_bcci_simulation(), mvn_mar_20_nb_bcci_task(), mvn_mar_20_nb_pcci_simulation(), mvn_mar_20_nb_pcci_task(), mvn_mar_20_nb_simulation(), mvn_mar_20_nb_task(), mvn_mar_20_nbbc.fiml_simulation(), mvn_mar_20_nbbc.fiml_task(), mvn_mar_20_nbpc.fiml_simulation(), mvn_mar_20_nbpc.fiml_task(), mvn_mar_20_nb(), mvn_mar_30_nb.del_bcci_simulation(), mvn_mar_30_nb.del_bcci_task(), mvn_mar_30_nb.del_pcci_simulation(), mvn_mar_30_nb.del_pcci_task(), mvn_mar_30_nb.del_simulation(), mvn_mar_30_nb.del_task(), mvn_mar_30_nb.del(), mvn_mar_30_nb.fiml_bcci_simulation(), mvn_mar_30_nb.fiml_pcci_simulation(), mvn_mar_30_nb_bcci_simulation(), mvn_mar_30_nb_bcci_task(), mvn_mar_30_nb_pcci_simulation(), mvn_mar_30_nb_pcci_task(), mvn_mar_30_nb_simulation(), mvn_mar_30_nb_task(), mvn_mar_30_nbbc.fiml_simulation(), mvn_mar_30_nbbc.fiml_task(), mvn_mar_30_nbpc.fiml_simulation(), mvn_mar_30_nbpc.fiml_task(), mvn_mar_30_nb(), mvn_mcar_10_nb.del_bcci_simulation(), mvn_mcar_10_nb.del_bcci_task(), mvn_mcar_10_nb.del_pcci_simulation(), mvn_mcar_10_nb.del_pcci_task(), mvn_mcar_10_nb.del_simulation(), mvn_mcar_10_nb.del_task(), mvn_mcar_10_nb.del(), mvn_mcar_10_nb.fiml_bcci_simulation(), mvn_mcar_10_nb.fiml_pcci_simulation(), mvn_mcar_10_nb_bcci_simulation(), mvn_mcar_10_nb_bcci_task(), mvn_mcar_10_nb_pcci_simulation(), mvn_mcar_10_nb_pcci_task(), mvn_mcar_10_nb_simulation(), mvn_mcar_10_nb_task(), mvn_mcar_10_nbbc.fiml_simulation(), mvn_mcar_10_nbbc.fiml_task(), mvn_mcar_10_nbpc.fiml_simulation(), mvn_mcar_10_nbpc.fiml_task(), mvn_mcar_10_nb(), mvn_mcar_20_nb.del_bcci_simulation(), mvn_mcar_20_nb.del_bcci_task(), mvn_mcar_20_nb.del_pcci_simulation(), mvn_mcar_20_nb.del_pcci_task(), mvn_mcar_20_nb.del_simulation(), mvn_mcar_20_nb.del_task(), mvn_mcar_20_nb.del(), mvn_mcar_20_nb.fiml_bcci_simulation(), mvn_mcar_20_nb.fiml_pcci_simulation(), mvn_mcar_20_nb_bcci_simulation(), mvn_mcar_20_nb_bcci_task(), mvn_mcar_20_nb_pcci_simulation(), mvn_mcar_20_nb_pcci_task(), mvn_mcar_20_nb_simulation(), mvn_mcar_20_nb_task(), mvn_mcar_20_nbbc.fiml_simulation(), mvn_mcar_20_nbbc.fiml_task(), mvn_mcar_20_nbpc.fiml_simulation(), mvn_mcar_20_nbpc.fiml_task(), mvn_mcar_20_nb(), mvn_mcar_30_nb.del_bcci_simulation(), mvn_mcar_30_nb.del_bcci_task(), mvn_mcar_30_nb.del_pcci_simulation(), mvn_mcar_30_nb.del_pcci_task(), mvn_mcar_30_nb.del_simulation(), mvn_mcar_30_nb.del_task(), mvn_mcar_30_nb.del(), mvn_mcar_30_nb.fiml_bcci_simulation(), mvn_mcar_30_nb.fiml_pcci_simulation(), mvn_mcar_30_nb_bcci_simulation(), mvn_mcar_30_nb_bcci_task(), mvn_mcar_30_nb_pcci_simulation(), mvn_mcar_30_nb_pcci_task(), mvn_mcar_30_nb_simulation(), mvn_mcar_30_nb_task(), mvn_mcar_30_nbbc.fiml_simulation(), mvn_mcar_30_nbbc.fiml_task(), mvn_mcar_30_nbpc.fiml_simulation(), mvn_mcar_30_nbpc.fiml_task(), mvn_mcar_30_nb(), mvn_mnar_10_nb.del_bcci_simulation(), mvn_mnar_10_nb.del_bcci_task(), mvn_mnar_10_nb.del_pcci_simulation(), mvn_mnar_10_nb.del_pcci_task(), mvn_mnar_10_nb.del_simulation(), mvn_mnar_10_nb.del_task(), mvn_mnar_10_nb.del(), mvn_mnar_10_nb.fiml_bcci_simulation(), mvn_mnar_10_nb.fiml_pcci_simulation(), mvn_mnar_10_nb_bcci_simulation(), mvn_mnar_10_nb_bcci_task(), mvn_mnar_10_nb_pcci_simulation(), mvn_mnar_10_nb_pcci_task(), mvn_mnar_10_nb_simulation(), mvn_mnar_10_nb_task(), mvn_mnar_10_nbbc.fiml_simulation(), mvn_mnar_10_nbbc.fiml_task(), mvn_mnar_10_nbpc.fiml_simulation(), mvn_mnar_10_nbpc.fiml_task(), mvn_mnar_10_nb(), mvn_mnar_20_nb.del_bcci_simulation(), mvn_mnar_20_nb.del_bcci_task(), mvn_mnar_20_nb.del_pcci_simulation(), mvn_mnar_20_nb.del_pcci_task(), mvn_mnar_20_nb.del_simulation(), mvn_mnar_20_nb.del_task(), mvn_mnar_20_nb.del(), mvn_mnar_20_nb.fiml_bcci_simulation(), mvn_mnar_20_nb.fiml_pcci_simulation(), mvn_mnar_20_nb_bcci_simulation(), mvn_mnar_20_nb_bcci_task(), mvn_mnar_20_nb_pcci_simulation(), mvn_mnar_20_nb_pcci_task(), mvn_mnar_20_nb_simulation(), mvn_mnar_20_nb_task(), mvn_mnar_20_nbbc.fiml_simulation(), mvn_mnar_20_nbbc.fiml_task(), mvn_mnar_20_nbpc.fiml_simulation(), mvn_mnar_20_nbpc.fiml_task(), mvn_mnar_20_nb(), mvn_mnar_30_nb.del_bcci_simulation(), mvn_mnar_30_nb.del_bcci_task(), mvn_mnar_30_nb.del_pcci_simulation(), mvn_mnar_30_nb.del_pcci_task(), mvn_mnar_30_nb.del_simulation(), mvn_mnar_30_nb.del_task(), mvn_mnar_30_nb.del(), mvn_mnar_30_nb.fiml_bcci_simulation(), mvn_mnar_30_nb.fiml_pcci_simulation(), mvn_mnar_30_nb_bcci_simulation(), mvn_mnar_30_nb_bcci_task(), mvn_mnar_30_nb_pcci_simulation(), mvn_mnar_30_nb_pcci_task(), mvn_mnar_30_nb_simulation(), mvn_mnar_30_nb_task(), mvn_mnar_30_nbbc.fiml_simulation(), mvn_mnar_30_nbbc.fiml_task(), mvn_mnar_30_nbpc.fiml_simulation(), mvn_mnar_30_nbpc.fiml_task(), mvn_mnar_30_nb(), mvn_nb_bcaci_simulation(), mvn_nb_bcaci_task(), mvn_nb_bcci_simulation(), mvn_nb_bcci_task(), mvn_nb_pcci_simulation(), mvn_nb_pcci_task(), mvn_nb_simulation(), mvn_nb_task(), mvn_nb(), mvn_std_nb_bcaci_simulation(), mvn_std_nb_bcaci_task(), mvn_std_nb_bcci_simulation(), mvn_std_nb_bcci_task(), mvn_std_nb_pcci_simulation(), mvn_std_nb_pcci_task(), mvn_std_nb_simulation(), mvn_std_nb_task(), mvn_std_nb(), nb.del(), nb.fiml(), nbpc.fiml(), nb(), vm_mod_nb_bcaci_simulation(), vm_mod_nb_bcaci_task(), vm_mod_nb_bcci_simulation(), vm_mod_nb_bcci_task(), vm_mod_nb_pcci_simulation(), vm_mod_nb_pcci_task(), vm_mod_nb_simulation(), vm_mod_nb_task(), vm_mod_nb(), vm_mod_std_nb_bcaci_simulation(), vm_mod_std_nb_bcaci_task(), vm_mod_std_nb_bcci_simulation(), vm_mod_std_nb_bcci_task(), vm_mod_std_nb_pcci_simulation(), vm_mod_std_nb_pcci_task(), vm_mod_std_nb_simulation(), vm_mod_std_nb_task(), vm_mod_std_nb(), vm_sev_nb_bcaci_simulation(), vm_sev_nb_bcaci_task(), vm_sev_nb_bcci_simulation(), vm_sev_nb_bcci_task(), vm_sev_nb_pcci_simulation(), vm_sev_nb_pcci_task(), vm_sev_nb_simulation(), vm_sev_nb_task(), vm_sev_nb(), vm_sev_std_nb_bcaci_simulation(), vm_sev_std_nb_bcaci_task(), vm_sev_std_nb_bcci_simulation(), vm_sev_std_nb_bcci_task(), vm_sev_std_nb_pcci_simulation(), vm_sev_std_nb_pcci_task(), vm_sev_std_nb_simulation(), vm_sev_std_nb_task(), vm_sev_std_nb()

Author

Ivan Jacob Agaloos Pesigan

Examples

taskid <- 1 data <- mvn_dat(taskid = taskid) nbbc.fiml(data = mvn_mcar_10_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.537000 0.026000 5000.000000 NA 0.474000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.487000 0.588000 0.603000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.129000 0.101000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.047619 1.020000 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902
nbbc.fiml(data = mvn_mcar_20_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.538000 0.026000 5000.000000 NA 0.470000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.487000 0.592000 0.608000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.138000 0.105000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.029412 1.058824 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902
nbbc.fiml(data = mvn_mcar_30_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.531000 0.027000 5000.000000 NA 0.465000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.478000 0.585000 0.605000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.140000 0.107000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.121212 1.018868 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902
nbbc.fiml(data = mvn_mar_10_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.527000 0.026000 5000.000000 NA 0.463000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.477000 0.578000 0.594000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.131000 0.101000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.046875 1.020000 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902
nbbc.fiml(data = mvn_mar_20_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.532000 0.026000 5000.000000 NA 0.468000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.481000 0.586000 0.603000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.135000 0.105000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.109375 1.058824 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902
nbbc.fiml(data = mvn_mar_30_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.548000 0.027000 5000.000000 NA 0.479000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.495000 0.601000 0.620000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.141000 0.106000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.043478 1.000000 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902
nbbc.fiml(data = mvn_mnar_10_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.521000 0.025000 5000.000000 NA 0.458000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.471000 0.571000 0.587000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.129000 0.100000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.047619 1.000000 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902
nbbc.fiml(data = mvn_mnar_20_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.543000 0.027000 5000.000000 NA 0.474000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.490000 0.596000 0.613000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.139000 0.106000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.014493 1.000000 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902
nbbc.fiml(data = mvn_mnar_30_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.523000 0.027000 5000.000000 NA 0.457000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.471000 0.577000 0.597000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.140000 0.106000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.121212 1.038462 NA 1.000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.000000 NA 0.000000 0.000000 0.509902