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

nbpc.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(), nbbc.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) nbpc.fiml(data = mvn_mcar_10_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.501000 0.027000 5000.000000 NA 0.435000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.449000 0.554000 0.575000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.140000 0.105000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.121212 1.019231 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
nbpc.fiml(data = mvn_mcar_20_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.504000 0.027000 5000.000000 NA 0.434000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.452000 0.558000 0.578000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.144000 0.106000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.057143 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
nbpc.fiml(data = mvn_mcar_30_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.503000 0.028000 5000.000000 NA 0.433000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.449000 0.560000 0.579000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.146000 0.111000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.085714 1.055556 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
nbpc.fiml(data = mvn_mar_10_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.510000 0.027000 5000.000000 NA 0.443000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.458000 0.563000 0.582000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.139000 0.105000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.074627 1.019231 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
nbpc.fiml(data = mvn_mar_20_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.509000 0.027000 5000.000000 NA 0.441000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.456000 0.564000 0.580000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.139000 0.108000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.044118 1.037736 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
nbpc.fiml(data = mvn_mar_30_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.529000 0.028000 5000.000000 NA 0.457000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.474000 0.587000 0.606000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.149000 0.113000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.069444 1.054545 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
nbpc.fiml(data = mvn_mnar_10_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.502000 0.027000 5000.000000 NA 0.435000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.451000 0.556000 0.576000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.141000 0.105000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.104478 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
nbpc.fiml(data = mvn_mnar_20_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.531000 0.027000 5000.000000 NA 0.461000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.479000 0.587000 0.602000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.141000 0.108000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.014286 1.076923 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
nbpc.fiml(data = mvn_mnar_30_dat(data = data, taskid = taskid), taskid = taskid)
#> est se reps ci_0.05 ci_0.5 #> 0.516000 0.028000 5000.000000 NA 0.445000 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.462000 0.572000 0.588000 NA NA #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.000000 0.000000 NA 0.143000 0.110000 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> NA 1.014085 1.037037 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