# Bayesian CFA of the RIASEC42 #
library(foreign)
library(plyr)
library(blavaan)
## Loading required package: Rcpp
## This is blavaan 0.5-3
## On multicore systems, we suggest use of future::plan("multicore") or
## future::plan("multisession") for faster post-MCMC computations.
library(semTools)
## Loading required package: lavaan
## This is lavaan 0.6-17
## lavaan is FREE software! Please report any bugs.
##
## ###############################################################################
## This is semTools 0.5-6
## All users of R (or SEM) are invited to submit functions or ideas for functions.
## ###############################################################################
library(rstan)
## Loading required package: StanHeaders
##
## rstan version 2.32.6 (Stan version 2.32.2)
## For execution on a local, multicore CPU with excess RAM we recommend calling
## options(mc.cores = parallel::detectCores()).
## To avoid recompilation of unchanged Stan programs, we recommend calling
## rstan_options(auto_write = TRUE)
## For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions,
## change `threads_per_chain` option:
## rstan_options(threads_per_chain = 1)
## Do not specify '-march=native' in 'LOCAL_CPPFLAGS' or a Makevars file
library(ggplot2)
library(HDInterval)
library(mcmcse)
library(Rmpfr)
## Loading required package: gmp
##
## Attaching package: 'gmp'
## The following objects are masked from 'package:base':
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## %*%, apply, crossprod, matrix, tcrossprod
## C code of R package 'Rmpfr': GMP using 64 bits per limb
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## Attaching package: 'Rmpfr'
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library(scales)
library(gridExtra)
library(epiDisplay)
## Loading required package: survival
## Loading required package: MASS
## Loading required package: nnet
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## Attaching package: 'epiDisplay'
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library(bayesplot)
## This is bayesplot version 1.11.1
## - Online documentation and vignettes at mc-stan.org/bayesplot
## - bayesplot theme set to bayesplot::theme_default()
## * Does _not_ affect other ggplot2 plots
## * See ?bayesplot_theme_set for details on theme setting
library(Bayesrel)
RIASEC42 = read.csv2("D:\\OneDrive - UMP\\R - lenh 2016\\RIASEC1308.csv", comment.char="#", stringsAsFactors=T)
names(RIASEC42)
## [1] "id" "gioi" "lop" "R1" "R2" "R3" "R4" "R5" "R6" "R7"
## [11] "I1" "I2" "I3" "I4" "I5" "I6" "I7" "A1" "A2" "A3"
## [21] "A4" "A5" "A6" "A7" "S1" "S2" "S3" "S4" "S5" "S6"
## [31] "S7" "E1" "E2" "E3" "E4" "E5" "E6" "E7" "C1" "C2"
## [41] "C3" "C4" "C5" "C6" "C7"
# Định nghĩa mô hình SEM
mohinh.1 <- '
R =~ R1 + R2 + R3 + R4 + R5 + R6 + R7
I =~ I1 + I2 + I3 + I4 + I5 + I6 + I7
A =~ A1 + A2 + A3 + A4 + A5 + S6 + A7
S =~ S1 + S2 + S3 + S4 + S5 + S6 + S7
E =~ E1 + E2 + E3 + E4 + E5 + E6 + E7
C =~ C1 + C2 + C3 + C4 + C5 + C6 + C7 '
library(blcfa)
## Loading required package: stringr
## Loading required package: MCMCpack
## Loading required package: coda
##
## Attaching package: 'coda'
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## traceplot
## ##
## ## Markov Chain Monte Carlo Package (MCMCpack)
## ## Copyright (C) 2003-2024 Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park
## ##
## ## Support provided by the U.S. National Science Foundation
## ## (Grants SES-0350646 and SES-0350613)
## ##
## Loading required package: msm
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## summarize
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## Loading required package: MplusAutomation
## Version: 1.1.1
## We work hard to write this free software. Please help us get credit by citing:
##
## Hallquist, M. N. & Wiley, J. F. (2018). MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus. Structural Equation Modeling, 25, 621-638. doi: 10.1080/10705511.2017.1402334.
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## -- see citation("MplusAutomation").
## Loading required package: sna
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## Attaching package: 'statnet.common'
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## Loading required package: network
##
## 'network' 1.18.2 (2023-12-04), part of the Statnet Project
## * 'news(package="network")' for changes since last version
## * 'citation("network")' for citation information
## * 'https://statnet.org' for help, support, and other information
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## Attaching package: 'network'
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## is.discrete
## sna: Tools for Social Network Analysis
## Version 2.7-2 created on 2023-12-05.
## copyright (c) 2005, Carter T. Butts, University of California-Irvine
## For citation information, type citation("sna").
## Type help(package="sna") to get started.
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## Attaching package: 'sna'
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## Loading required package: rstudioapi
fit.1 <- bcfa(
model = mohinh.1, # Mô hình SEM được định nghĩa trước
data = RIASEC42, # Dữ liệu đầu vào
cp = "srs", # Phương pháp chọn mẫu ("srs": Simple Random Sampling)
n.chains = 1, # Số lượng chuỗi lấy mẫu
burnin = 100, # Số lần lấy mẫu ban đầu bị bỏ qua
sample = 1000, # Số lượng lần lấy mẫu
mcmcfile = TRUE, # Lưu trữ kết quả MCMC vào tệp tin
mcmcextra = list(), # Thông số bổ sung cho MCMC
inits = "simple", # Cách khởi tạo (ở đây sử dụng cách khởi tạo đơn giản)
convergence = "flexible", # Tiêu chí hội tụ (ở đây sử dụng cách kiểm tra hội tụ thủ công)
seed = 12345, # Seed cho quá trình ngẫu nhiên
target = "stan", # Phương pháp lấy mẫu từ Stan
wiggle.sd = 0.1, # Độ biến động cho phép
prisamp = TRUE, # Lấy mẫu đều từ các nhóm phụ
jags.ic = TRUE, # Sử dụng thông số tương quan từ JAGS
test = "bootstrap" # Phương pháp kiểm định (ở đây sử dụng kiểm định bootstrap)
)
##
## SAMPLING FOR MODEL 'stanmarg' NOW (CHAIN 1).
## Chain 1:
## Chain 1: Gradient evaluation took 0.007457 seconds
## Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 74.57 seconds.
## Chain 1: Adjust your expectations accordingly!
## Chain 1:
## Chain 1:
## Chain 1: WARNING: There aren't enough warmup iterations to fit the
## Chain 1: three stages of adaptation as currently configured.
## Chain 1: Reducing each adaptation stage to 15%/75%/10% of
## Chain 1: the given number of warmup iterations:
## Chain 1: init_buffer = 15
## Chain 1: adapt_window = 75
## Chain 1: term_buffer = 10
## Chain 1:
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## Chain 1:
## Chain 1: Elapsed Time: 122.876 seconds (Warm-up)
## Chain 1: 761.694 seconds (Sampling)
## Chain 1: 884.57 seconds (Total)
## Chain 1:
## Computing post-estimation metrics (including lvs if requested)...
Hiển thị kết quả mô hình
summary(fit.1) # Hiển thị tổng quan về kết quả mô hình
## blavaan 0.5.3 ended normally after 1000 iterations
##
## Estimator BAYES
## Optimization method MCMC
## Number of model parameters 98
##
## Number of observations 1308
##
## Statistic MargLogLik PPP
## Value -112000.180 0.000
##
## Parameter Estimates:
##
##
## Latent Variables:
## Estimate Pri.SD pi.lower pi.upper Rhat Prior
## R =~
## R1 1.000 0.000
## R2 0.238 9.823 -19.806 18.812 1.000 normal(0,10)
## R3 -0.193 9.644 -19.539 19.716 0.999 normal(0,10)
## R4 -0.157 9.643 -18.468 19.228 0.999 normal(0,10)
## R5 0.376 10.164 -19.807 20.579 0.999 normal(0,10)
## R6 0.346 9.719 -18.632 18.094 0.999 normal(0,10)
## R7 -0.087 10.203 -18.904 19.779 0.999 normal(0,10)
## I =~
## I1 1.000 0.000
## I2 0.069 9.698 -19.300 19.184 0.999 normal(0,10)
## I3 -0.314 9.541 -18.501 18.523 0.999 normal(0,10)
## I4 -0.254 10.146 -19.743 19.282 0.999 normal(0,10)
## I5 0.155 9.633 -17.967 19.415 1.001 normal(0,10)
## I6 0.057 10.051 -20.546 18.788 0.999 normal(0,10)
## I7 -0.187 10.422 -20.279 19.664 0.999 normal(0,10)
## A =~
## A1 1.000 0.000
## A2 -0.065 9.860 -19.289 18.893 0.999 normal(0,10)
## A3 0.100 10.074 -18.928 19.687 0.999 normal(0,10)
## A4 -0.413 10.286 -21.059 19.543 0.999 normal(0,10)
## A5 0.374 9.658 -19.217 19.712 0.999 normal(0,10)
## S6 -0.505 9.519 -19.731 18.531 0.999 normal(0,10)
## A7 -0.295 10.692 -22.597 20.582 0.999 normal(0,10)
## S =~
## S1 1.000 0.000
## S2 -0.076 9.654 -18.766 19.516 1.000 normal(0,10)
## S3 0.412 9.475 -19.302 19.038 0.999 normal(0,10)
## S4 -0.414 9.466 -18.212 17.475 0.999 normal(0,10)
## S5 -0.321 10.180 -20.108 20.925 1.000 normal(0,10)
## S6 0.191 10.008 -20.324 20.277 1.001 normal(0,10)
## S7 0.357 9.985 -18.815 20.474 0.999 normal(0,10)
## E =~
## E1 1.000 0.000
## E2 -0.393 10.313 -19.958 20.268 0.999 normal(0,10)
## E3 -0.424 10.570 -23.032 20.044 0.999 normal(0,10)
## E4 -0.207 9.420 -19.284 18.471 0.999 normal(0,10)
## E5 -0.657 10.150 -19.787 19.622 0.999 normal(0,10)
## E6 0.058 10.592 -19.967 20.452 0.999 normal(0,10)
## E7 0.147 9.225 -18.709 18.334 1.000 normal(0,10)
## C =~
## C1 1.000 0.000
## C2 -0.128 9.906 -18.820 19.796 0.999 normal(0,10)
## C3 0.071 10.200 -19.842 19.292 0.999 normal(0,10)
## C4 0.356 9.684 -18.580 18.611 0.999 normal(0,10)
## C5 -0.189 9.633 -20.128 18.707 0.999 normal(0,10)
## C6 0.040 9.570 -18.754 19.166 0.999 normal(0,10)
## C7 0.253 9.824 -19.870 19.938 0.999 normal(0,10)
##
## Covariances:
## Estimate Pri.SD pi.lower pi.upper Rhat Prior
## R ~~
## I 0.055 2.581 -6.227 5.287 0.999 lkj_corr(1)
## A -0.051 3.425 -5.610 5.655 0.999 lkj_corr(1)
## S 0.051 3.124 -5.995 6.049 0.999 lkj_corr(1)
## E -0.116 3.060 -7.291 6.474 1.000 lkj_corr(1)
## C 0.076 3.818 -5.156 5.443 0.999 lkj_corr(1)
## I ~~
## A 0.074 3.116 -4.973 6.094 1.001 lkj_corr(1)
## S 0.030 2.595 -4.341 4.823 1.000 lkj_corr(1)
## E -0.143 3.054 -6.283 5.250 1.000 lkj_corr(1)
## C -0.063 2.668 -5.407 4.216 0.999 lkj_corr(1)
## A ~~
## S 0.040 2.933 -6.093 6.492 1.001 lkj_corr(1)
## E -0.100 3.335 -6.126 5.243 1.002 lkj_corr(1)
## C -0.004 3.025 -5.615 5.385 1.001 lkj_corr(1)
## S ~~
## E -0.009 3.095 -5.813 5.382 0.999 lkj_corr(1)
## C 0.057 3.100 -4.820 5.491 1.001 lkj_corr(1)
## E ~~
## C -0.047 3.114 -5.744 5.093 0.999 lkj_corr(1)
##
## Variances:
## Estimate Pri.SD pi.lower pi.upper Rhat Prior
## .R1 7.916 16.572 0.007 52.541 0.999 gamma(1,.5)[sd]
## .R2 8.117 18.570 0.003 55.390 1.000 gamma(1,.5)[sd]
## .R3 8.174 19.768 0.002 56.848 0.999 gamma(1,.5)[sd]
## .R4 7.155 16.653 0.001 42.677 1.004 gamma(1,.5)[sd]
## .R5 7.670 15.221 0.004 50.447 0.999 gamma(1,.5)[sd]
## .R6 8.154 16.962 0.003 52.365 1.001 gamma(1,.5)[sd]
## .R7 7.718 15.363 0.007 48.840 0.999 gamma(1,.5)[sd]
## .I1 8.612 19.322 0.004 57.814 1.000 gamma(1,.5)[sd]
## .I2 7.287 17.424 0.001 47.445 0.999 gamma(1,.5)[sd]
## .I3 8.697 19.447 0.001 62.136 1.003 gamma(1,.5)[sd]
## .I4 8.704 20.135 0.002 65.780 1.005 gamma(1,.5)[sd]
## .I5 6.357 11.922 0.003 38.933 1.000 gamma(1,.5)[sd]
## .I6 8.170 23.102 0.003 49.787 1.000 gamma(1,.5)[sd]
## .I7 8.986 30.889 0.001 66.143 1.000 gamma(1,.5)[sd]
## .A1 8.021 17.231 0.005 54.712 0.999 gamma(1,.5)[sd]
## .A2 8.134 20.271 0.002 58.003 1.002 gamma(1,.5)[sd]
## .A3 8.769 22.493 0.006 54.394 0.999 gamma(1,.5)[sd]
## .A4 8.034 18.143 0.006 58.459 0.999 gamma(1,.5)[sd]
## .A5 9.019 20.305 0.003 64.088 0.999 gamma(1,.5)[sd]
## .S6 7.830 16.556 0.005 51.864 0.999 gamma(1,.5)[sd]
## .A7 8.104 17.726 0.001 52.462 1.000 gamma(1,.5)[sd]
## .S1 9.322 23.031 0.002 64.356 1.001 gamma(1,.5)[sd]
## .S2 7.437 15.640 0.005 49.060 1.000 gamma(1,.5)[sd]
## .S3 7.264 14.312 0.003 48.928 1.000 gamma(1,.5)[sd]
## .S4 7.916 18.349 0.002 46.108 0.999 gamma(1,.5)[sd]
## .S5 7.482 14.760 0.007 47.402 1.000 gamma(1,.5)[sd]
## .S7 7.691 18.844 0.002 50.723 0.999 gamma(1,.5)[sd]
## .E1 7.642 15.154 0.003 49.147 1.001 gamma(1,.5)[sd]
## .E2 7.622 14.298 0.003 49.552 0.999 gamma(1,.5)[sd]
## .E3 8.202 18.094 0.002 52.753 0.999 gamma(1,.5)[sd]
## .E4 7.966 16.162 0.004 49.126 0.999 gamma(1,.5)[sd]
## .E5 8.150 16.261 0.001 56.676 1.001 gamma(1,.5)[sd]
## .E6 7.802 15.758 0.003 50.992 0.999 gamma(1,.5)[sd]
## .E7 7.914 19.212 0.002 64.554 0.999 gamma(1,.5)[sd]
## .C1 8.244 19.316 0.004 52.512 1.001 gamma(1,.5)[sd]
## .C2 7.473 16.614 0.003 47.650 0.999 gamma(1,.5)[sd]
## .C3 8.143 16.744 0.007 53.399 1.000 gamma(1,.5)[sd]
## .C4 7.462 14.567 0.002 53.533 0.999 gamma(1,.5)[sd]
## .C5 9.021 19.379 0.002 62.055 1.000 gamma(1,.5)[sd]
## .C6 9.122 26.157 0.002 59.966 1.000 gamma(1,.5)[sd]
## .C7 7.588 16.244 0.002 45.813 0.999 gamma(1,.5)[sd]
## R 9.318 22.174 0.002 58.778 0.999 gamma(1,.5)[sd]
## I 7.335 14.076 0.005 43.178 0.999 gamma(1,.5)[sd]
## A 8.199 17.759 0.004 58.152 1.001 gamma(1,.5)[sd]
## S 8.076 17.721 0.002 59.394 1.000 gamma(1,.5)[sd]
## E 8.128 15.767 0.005 51.536 0.999 gamma(1,.5)[sd]
## C 7.450 18.886 0.002 47.380 0.999 gamma(1,.5)[sd]
summary(fit.1, standardized = T) # Hiển thị kết quả standardized (chuẩn hóa)
## blavaan 0.5.3 ended normally after 1000 iterations
##
## Estimator BAYES
## Optimization method MCMC
## Number of model parameters 98
##
## Number of observations 1308
##
## Statistic MargLogLik PPP
## Value -112000.180 0.000
##
## Parameter Estimates:
##
##
## Latent Variables:
## Estimate Pri.SD pi.lower pi.upper Std.lv Std.all
## R =~
## R1 1.000 0.000 3.053 0.735
## R2 0.238 9.823 -19.806 18.812 0.726 0.247
## R3 -0.193 9.644 -19.539 19.716 -0.588 -0.202
## R4 -0.157 9.643 -18.468 19.228 -0.478 -0.176
## R5 0.376 10.164 -19.807 20.579 1.148 0.383
## R6 0.346 9.719 -18.632 18.094 1.057 0.347
## R7 -0.087 10.203 -18.904 19.779 -0.265 -0.095
## I =~
## I1 1.000 0.000 2.708 0.678
## I2 0.069 9.698 -19.300 19.184 0.186 0.069
## I3 -0.314 9.541 -18.501 18.523 -0.849 -0.277
## I4 -0.254 10.146 -19.743 19.282 -0.689 -0.227
## I5 0.155 9.633 -17.967 19.415 0.421 0.165
## I6 0.057 10.051 -20.546 18.788 0.155 0.054
## I7 -0.187 10.422 -20.279 19.664 -0.507 -0.167
## A =~
## A1 1.000 0.000 2.863 0.711
## A2 -0.065 9.860 -19.289 18.893 -0.185 -0.065
## A3 0.100 10.074 -18.928 19.687 0.286 0.096
## A4 -0.413 10.286 -21.059 19.543 -1.182 -0.385
## A5 0.374 9.658 -19.217 19.712 1.070 0.335
## S6 -0.505 9.519 -19.731 18.531 -1.445 -0.452
## A7 -0.295 10.692 -22.597 20.582 -0.843 -0.284
## S =~
## S1 1.000 0.000 2.842 0.681
## S2 -0.076 9.654 -18.766 19.516 -0.216 -0.079
## S3 0.412 9.475 -19.302 19.038 1.171 0.398
## S4 -0.414 9.466 -18.212 17.475 -1.177 -0.386
## S5 -0.321 10.180 -20.108 20.925 -0.914 -0.317
## S6 0.191 10.008 -20.324 20.277 0.542 0.170
## S7 0.357 9.985 -18.815 20.474 1.014 0.344
## E =~
## E1 1.000 0.000 2.851 0.718
## E2 -0.393 10.313 -19.958 20.268 -1.120 -0.376
## E3 -0.424 10.570 -23.032 20.044 -1.210 -0.389
## E4 -0.207 9.420 -19.284 18.471 -0.591 -0.205
## E5 -0.657 10.150 -19.787 19.622 -1.872 -0.548
## E6 0.058 10.592 -19.967 20.452 0.164 0.059
## E7 0.147 9.225 -18.709 18.334 0.418 0.147
## C =~
## C1 1.000 0.000 2.729 0.689
## C2 -0.128 9.906 -18.820 19.796 -0.348 -0.126
## C3 0.071 10.200 -19.842 19.292 0.193 0.068
## C4 0.356 9.684 -18.580 18.611 0.972 0.335
## C5 -0.189 9.633 -20.128 18.707 -0.517 -0.170
## C6 0.040 9.570 -18.754 19.166 0.108 0.036
## C7 0.253 9.824 -19.870 19.938 0.691 0.243
## Rhat Prior
##
##
## 1.000 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
##
##
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 1.001 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
##
##
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
##
##
## 1.000 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 1.000 normal(0,10)
## 1.001 normal(0,10)
## 0.999 normal(0,10)
##
##
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 1.000 normal(0,10)
##
##
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
## 0.999 normal(0,10)
##
## Covariances:
## Estimate Pri.SD pi.lower pi.upper Std.lv Std.all
## R ~~
## I 0.055 2.581 -6.227 5.287 0.007 0.007
## A -0.051 3.425 -5.610 5.655 -0.006 -0.006
## S 0.051 3.124 -5.995 6.049 0.006 0.006
## E -0.116 3.060 -7.291 6.474 -0.013 -0.013
## C 0.076 3.818 -5.156 5.443 0.009 0.009
## I ~~
## A 0.074 3.116 -4.973 6.094 0.010 0.010
## S 0.030 2.595 -4.341 4.823 0.004 0.004
## E -0.143 3.054 -6.283 5.250 -0.018 -0.018
## C -0.063 2.668 -5.407 4.216 -0.009 -0.009
## A ~~
## S 0.040 2.933 -6.093 6.492 0.005 0.005
## E -0.100 3.335 -6.126 5.243 -0.012 -0.012
## C -0.004 3.025 -5.615 5.385 -0.001 -0.001
## S ~~
## E -0.009 3.095 -5.813 5.382 -0.001 -0.001
## C 0.057 3.100 -4.820 5.491 0.007 0.007
## E ~~
## C -0.047 3.114 -5.744 5.093 -0.006 -0.006
## Rhat Prior
##
## 0.999 lkj_corr(1)
## 0.999 lkj_corr(1)
## 0.999 lkj_corr(1)
## 1.000 lkj_corr(1)
## 0.999 lkj_corr(1)
##
## 1.001 lkj_corr(1)
## 1.000 lkj_corr(1)
## 1.000 lkj_corr(1)
## 0.999 lkj_corr(1)
##
## 1.001 lkj_corr(1)
## 1.002 lkj_corr(1)
## 1.001 lkj_corr(1)
##
## 0.999 lkj_corr(1)
## 1.001 lkj_corr(1)
##
## 0.999 lkj_corr(1)
##
## Variances:
## Estimate Pri.SD pi.lower pi.upper Std.lv Std.all
## .R1 7.916 16.572 0.007 52.541 7.916 0.459
## .R2 8.117 18.570 0.003 55.390 8.117 0.939
## .R3 8.174 19.768 0.002 56.848 8.174 0.959
## .R4 7.155 16.653 0.001 42.677 7.155 0.969
## .R5 7.670 15.221 0.004 50.447 7.670 0.853
## .R6 8.154 16.962 0.003 52.365 8.154 0.880
## .R7 7.718 15.363 0.007 48.840 7.718 0.991
## .I1 8.612 19.322 0.004 57.814 8.612 0.540
## .I2 7.287 17.424 0.001 47.445 7.287 0.995
## .I3 8.697 19.447 0.001 62.136 8.697 0.923
## .I4 8.704 20.135 0.002 65.780 8.704 0.948
## .I5 6.357 11.922 0.003 38.933 6.357 0.973
## .I6 8.170 23.102 0.003 49.787 8.170 0.997
## .I7 8.986 30.889 0.001 66.143 8.986 0.972
## .A1 8.021 17.231 0.005 54.712 8.021 0.495
## .A2 8.134 20.271 0.002 58.003 8.134 0.996
## .A3 8.769 22.493 0.006 54.394 8.769 0.991
## .A4 8.034 18.143 0.006 58.459 8.034 0.852
## .A5 9.019 20.305 0.003 64.088 9.019 0.887
## .S6 7.830 16.556 0.005 51.864 7.830 0.767
## .A7 8.104 17.726 0.001 52.462 8.104 0.919
## .S1 9.322 23.031 0.002 64.356 9.322 0.536
## .S2 7.437 15.640 0.005 49.060 7.437 0.994
## .S3 7.264 14.312 0.003 48.928 7.264 0.841
## .S4 7.916 18.349 0.002 46.108 7.916 0.851
## .S5 7.482 14.760 0.007 47.402 7.482 0.900
## .S7 7.691 18.844 0.002 50.723 7.691 0.882
## .E1 7.642 15.154 0.003 49.147 7.642 0.485
## .E2 7.622 14.298 0.003 49.552 7.622 0.859
## .E3 8.202 18.094 0.002 52.753 8.202 0.849
## .E4 7.966 16.162 0.004 49.126 7.966 0.958
## .E5 8.150 16.261 0.001 56.676 8.150 0.699
## .E6 7.802 15.758 0.003 50.992 7.802 0.997
## .E7 7.914 19.212 0.002 64.554 7.914 0.978
## .C1 8.244 19.316 0.004 52.512 8.244 0.525
## .C2 7.473 16.614 0.003 47.650 7.473 0.984
## .C3 8.143 16.744 0.007 53.399 8.143 0.995
## .C4 7.462 14.567 0.002 53.533 7.462 0.888
## .C5 9.021 19.379 0.002 62.055 9.021 0.971
## .C6 9.122 26.157 0.002 59.966 9.122 0.999
## .C7 7.588 16.244 0.002 45.813 7.588 0.941
## R 9.318 22.174 0.002 58.778 1.000 1.000
## I 7.335 14.076 0.005 43.178 1.000 1.000
## A 8.199 17.759 0.004 58.152 1.000 1.000
## S 8.076 17.721 0.002 59.394 1.000 1.000
## E 8.128 15.767 0.005 51.536 1.000 1.000
## C 7.450 18.886 0.002 47.380 1.000 1.000
## Rhat Prior
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.004 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.003 gamma(1,.5)[sd]
## 1.005 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.002 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
library(semPlot)
semPaths(
fit.1, # Đối tượng mô hình SEM được sử dụng để vẽ đồ thị
layout = "circle3", # Bố cục của đồ thị ("tree2", "tree3", "circle2", "circle3", "user")
whatLabels = "est", # Loại nhãn được hiển thị trên đường dẫn ("est", "std", "none")
intercepts = T, # Cho phép hiển thị hệ số điều chỉnh
residuals = T, # Cho phép hiển thị các sai số
intStyle = "rectangle", # Kiểu biểu tượng điều chỉnh ("ellipse", "triangle", "hexagon", "rectangle")
exoCov = TRUE, # Cho phép hiển thị hiệp phương sai của các biến endogenous
rotation = 3, # Góc quay của đồ thị
edge.label.cex = 1, # Kích thước của nhãn trên các cạnh
edge.label.color = "blue", # Màu của nhãn trên các cạnh
edge.label.font =.3, # Font của nhãn trên các cạnh
curvePivot = T, # Pivot curves around centroid
curveAdjacent = T, # Góc cong của các đường dẫn kề nhau
)
mô hình 2 hiêp biến số
Fit mô hình
mohinh.2 <- c(paste0("R", 1:7, " ~~ R", 1:7), paste0("R", 1:7, " ~ 1"),
paste0("I", 1:7, " ~~ I", 1:7), paste0("I", 1:7, " ~ 1"),
paste0("A", 1:7, " ~~ A", 1:7), paste0("A", 1:7, " ~ 1"),
paste0("S", 1:7, " ~~ S", 1:7), paste0("S", 1:7, " ~ 1"),
paste0("E", 1:7, " ~~ E", 1:7), paste0("E", 1:7, " ~ 1"),
paste0("C", 1:7, " ~~ C", 1:7), paste0("C", 1:7, " ~ 1"))
fit.2 <- bcfa(model = mohinh.2, # Mô hình SEM được định nghĩa trước
data = RIASEC42, # Dữ liệu đầu vào
cp = "srs", # Phương pháp chọn mẫu ("srs": Simple Random Sampling)
n.chains = 1, # Số lượng chuỗi lấy mẫu
burnin = 100, # Số lần lấy mẫu ban đầu bị bỏ qua
sample = 1000, # Số lượng lần lấy mẫu
mcmcfile = TRUE, # Lưu trữ kết quả MCMC vào tệp tin
mcmcextra = list(), # Thông số bổ sung cho MCMC
inits = "simple", # Cách khởi tạo (ở đây sử dụng cách khởi tạo đơn giản)
convergence="flexible", # Tiêu chí hội tụ (ở đây sử dụng cách kiểm tra hội tụ thủ công)
seed = 12345, # Seed cho quá trình ngẫu nhiên
target = "stan", # Phương pháp lấy mẫu từ Stan
wiggle.sd = 0.1, # Độ biến động cho phép
prisamp = TRUE, # Lấy mẫu đều từ các nhóm phụ
jags.ic = TRUE, # Sử dụng thông số tương quan từ JAGS
test = "bootstrap" # Phương pháp kiểm định (ở đây sử dụng kiểm định bootstrap)
)
##
## SAMPLING FOR MODEL 'stanmarg' NOW (CHAIN 1).
## Chain 1:
## Chain 1: Gradient evaluation took 0.005344 seconds
## Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 53.44 seconds.
## Chain 1: Adjust your expectations accordingly!
## Chain 1:
## Chain 1:
## Chain 1: WARNING: There aren't enough warmup iterations to fit the
## Chain 1: three stages of adaptation as currently configured.
## Chain 1: Reducing each adaptation stage to 15%/75%/10% of
## Chain 1: the given number of warmup iterations:
## Chain 1: init_buffer = 15
## Chain 1: adapt_window = 75
## Chain 1: term_buffer = 10
## Chain 1:
## Chain 1: Iteration: 1 / 1100 [ 0%] (Warmup)
## Chain 1: Iteration: 101 / 1100 [ 9%] (Sampling)
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## Chain 1: Iteration: 1100 / 1100 [100%] (Sampling)
## Chain 1:
## Chain 1: Elapsed Time: 222.925 seconds (Warm-up)
## Chain 1: 2804.99 seconds (Sampling)
## Chain 1: 3027.92 seconds (Total)
## Chain 1:
## Warning in validityMethod(object): The following variables have undefined
## values: log_lik[1],The following variables have undefined values:
## log_lik[2],The following variables have undefined values: log_lik[3],The
## following variables have undefined values: log_lik[4],The following variables
## have undefined values: log_lik[5],The following variables have undefined
## values: log_lik[6],The following variables have undefined values:
## log_lik[7],The following variables have undefined values: log_lik[8],The
## following variables have undefined values: log_lik[9],The following variables
## have undefined values: log_lik[10],The following variables have undefined
## values: log_lik[11],The following variables have undefined values:
## log_lik[12],The following variables have undefined values: log_lik[13],The
## following variables have undefined values: log_lik[14],The following variables
## have undefined values: log_lik[15],The following variables have undefined
## values: log_lik[16],The following variables have undefined values:
## log_lik[17],The following variables have undefined values: log_lik[18],The
## following variables have undefined values: log_lik[19],The following variables
## have undefined values: log_lik[20],The following variables have undefined
## values: log_lik[21],The following variables have undefined values:
## log_lik[22],The following variables have undefined values: log_lik[23],The
## following variables have undefined values: log_lik[24],The following variables
## have undefined values: log_lik[25],The following variables have undefined
## values: log_lik[26],The following variables have undefined values:
## log_lik[27],The following variables have undefined values: log_lik[28],The
## following variables have undefined values: log_lik[29],The following variables
## have undefined values: log_lik[30],The following variables have undefined
## values: log_lik[31],The following variables have undefined values:
## log_lik[32],The following variables have undefined values: log_lik[33],The
## following variables have undefined values: log_lik[34],The following variables
## have undefined values: log_lik[35],The following variables have undefined
## values: log_lik[36],The following variables have undefined values:
## log_lik[37],The following variables have undefined values: log_lik[38],The
## following variables have undefined values: log_lik[39],The following variables
## have undefined values: log_lik[40],The following variables have undefined
## values: log_lik[41],The following variables have undefined values:
## log_lik[42],The following variables have undefined values: log_lik[43],The
## following variables have undefined values: log_lik[44],The following variables
## have undefined values: log_lik[45],The following variables have undefined
## values: log_lik[46],The following variables have undefined values:
## log_lik[47],The following variables have undefined values: log_lik[48],The
## following variables have undefined values: log_lik[49],The following variables
## have undefined values: log_lik[50],The following variables have undefined
## values: log_lik[51],The following variables have undefined values:
## log_lik[52],The following variables have undefined values: log_lik[53],The
## following variables have undefined values: log_lik[54],The following variables
## have undefined values: log_lik[55],The following variables have undefined
## values: log_lik[56],The following variables have undefined values:
## log_lik[57],The following variables have undefined values: log_lik[58],The
## following variables have undefined values: log_lik[59],The following variables
## have undefined values: log_lik[60],The following variables have undefined
## values: log_lik[61],The following variables have undefined values:
## log_lik[62],The following variables have undefined values: log_lik[63],The
## following variables have undefined values: log_lik[64],The following variables
## have undefined values: log_lik[65],The following variables have undefined
## values: log_lik[66],The following variables have undefined values:
## log_lik[67],The following variables have undefined values: log_lik[68],The
## following variables have undefined values: log_lik[69],The following variables
## have undefined values: log_lik[70],The following variables have undefined
## values: log_lik[71],The following variables have undefined values:
## log_lik[72],The following variables have undefined values: log_lik[73],The
## following variables have undefined values: log_lik[74],The following variables
## have undefined values: log_lik[75],The following variables have undefined
## values: log_lik[76],The following variables have undefined values:
## log_lik[77],The following variables have undefined values: log_lik[78],The
## following variables have undefined values: log_lik[79],The following variables
## have undefined values: log_lik[80],The following variables have undefined
## values: log_lik[81],The following variables have undefined values:
## log_lik[82],The following variables have undefined values: log_lik[83],The
## following variables have undefined values: log_lik[84],The following variables
## have undefined values: log_lik[85],The following variables have undefined
## values: log_lik[86],The following variables have undefined values:
## log_lik[87],The following variables have undefined values: log_lik[88],The
## following variables have undefined values: log_lik[89],The following variables
## have undefined values: log_lik[90],The following variables have undefined
## values: log_lik[91],The following variables have undefined values:
## log_lik[92],The following variables have undefined values: log_lik[93],The
## following variables have undefined values: log_lik[94],The following variables
## have undefined values: log_lik[95],The following variables have undefined
## values: log_lik[96],The following variables have undefined values:
## log_lik[97],The following variables have undefined values: log_lik[98],The
## following variables have undefined values: log_lik[99],The following variables
## have undefined values: log_lik[100],The following variables have undefined
## values: log_lik[101],The following variables have undefined values:
## log_lik[102],The following variables have undefined values: log_lik[103],The
## following variables have undefined values: log_lik[104],The following variables
## have undefined values: log_lik[105],The following variables have undefined
## values: log_lik[106],The following variables have undefined values:
## log_lik[107],The following variables have undefined values: log_lik[108],The
## following variables have undefined values: log_lik[109],The following variables
## have undefined values: log_lik[110],The following variables have undefined
## values: log_lik[111],The following variables have undefined values:
## log_lik[112],The following variables have undefined values: log_lik[113],The
## following variables have undefined values: log_lik[114],The following variables
## have undefined values: log_lik[115],The following variables have undefined
## values: log_lik[116],The following variables have undefined values:
## log_lik[117],The following variables have undefined values: log_lik[118],The
## following variables have undefined values: log_lik[119],The following variables
## have undefined values: log_lik[120],The following variables have undefined
## values: log_lik[121],The following variables have undefined values:
## log_lik[122],The following variables have undefined values: log_lik[123],The
## following variables have undefined values: log_lik[124],The following variables
## have undefined values: log_lik[125],The following variables have undefined
## values: log_lik[126],The following variables have undefined values:
## log_lik[127],The following variables have undefined values: log_lik[128],The
## following variables have undefined values: log_lik[129],The following variables
## have undefined values: log_lik[130],The following variables have undefined
## values: log_lik[131],The following variables have undefined values:
## log_lik[132],The following variables have undefined values: log_lik[133],The
## following variables have undefined values: log_lik[134],The following variables
## have undefined values: log_lik[135],The following variables have undefined
## values: log_lik[136],Th
## Computing post-estimation metrics (including lvs if requested)...
Hiển thị kết quả mô hình
summary(fit.2) # Hiển thị tổng quan về kết quả mô hình
## blavaan 0.5.3 ended normally after 1000 iterations
##
## Estimator BAYES
## Optimization method MCMC
## Number of model parameters 84
##
## Number of observations 1308
##
## Statistic MargLogLik PPP
## Value -132232.297 1.000
##
## Parameter Estimates:
##
##
## Intercepts:
## Estimate Pri.SD pi.lower pi.upper Rhat Prior
## R1 -1.063 32.628 -61.995 63.410 0.999 normal(0,32)
## R2 -0.657 32.964 -67.529 65.255 0.999 normal(0,32)
## R3 -0.424 31.757 -57.857 63.731 1.000 normal(0,32)
## R4 0.261 31.829 -62.359 61.608 1.000 normal(0,32)
## R5 -0.862 33.151 -67.521 63.950 1.000 normal(0,32)
## R6 -1.795 33.591 -70.305 62.876 0.999 normal(0,32)
## R7 3.514 31.499 -59.742 64.656 0.999 normal(0,32)
## I1 0.617 32.611 -62.326 65.504 1.001 normal(0,32)
## I2 0.851 33.138 -63.501 64.477 1.000 normal(0,32)
## I3 0.862 32.486 -60.564 66.650 1.000 normal(0,32)
## I4 0.462 32.095 -61.927 67.962 1.000 normal(0,32)
## I5 1.042 31.082 -59.461 61.317 0.999 normal(0,32)
## I6 1.869 31.807 -61.999 64.056 1.000 normal(0,32)
## I7 0.583 31.328 -63.555 59.255 1.001 normal(0,32)
## A1 -0.561 31.282 -63.546 60.552 1.003 normal(0,32)
## A2 1.474 31.074 -59.263 61.042 1.000 normal(0,32)
## A3 -0.938 31.887 -62.854 58.912 1.000 normal(0,32)
## A4 -0.591 33.214 -66.325 61.916 1.000 normal(0,32)
## A5 0.176 33.469 -62.520 63.915 1.004 normal(0,32)
## A6 -0.283 30.365 -59.096 59.322 1.004 normal(0,32)
## A7 -1.285 32.003 -65.366 62.010 1.000 normal(0,32)
## S1 0.621 33.110 -65.669 64.110 0.999 normal(0,32)
## S2 -0.196 32.211 -61.040 64.220 0.999 normal(0,32)
## S3 -1.554 30.332 -60.309 60.543 1.001 normal(0,32)
## S4 -0.145 30.706 -60.627 59.787 0.999 normal(0,32)
## S5 1.146 32.718 -62.937 67.499 0.999 normal(0,32)
## S6 0.077 31.651 -67.503 62.157 1.001 normal(0,32)
## S7 1.126 32.331 -64.840 65.354 0.999 normal(0,32)
## E1 -0.265 32.176 -63.177 63.260 0.999 normal(0,32)
## E2 0.659 32.802 -61.124 63.116 0.999 normal(0,32)
## E3 -1.358 32.115 -64.996 60.666 1.000 normal(0,32)
## E4 0.419 32.395 -61.457 67.093 1.000 normal(0,32)
## E5 1.937 31.448 -59.076 65.302 1.000 normal(0,32)
## E6 -0.608 31.568 -61.931 62.379 0.999 normal(0,32)
## E7 -0.586 32.731 -65.141 61.871 0.999 normal(0,32)
## C1 -0.062 33.289 -64.676 70.423 0.999 normal(0,32)
## C2 0.750 32.485 -62.085 60.908 0.999 normal(0,32)
## C3 0.356 30.944 -58.157 67.297 0.999 normal(0,32)
## C4 1.074 32.009 -62.279 61.186 1.000 normal(0,32)
## C5 -0.676 32.216 -64.071 65.797 0.999 normal(0,32)
## C6 0.479 32.658 -65.222 61.289 0.999 normal(0,32)
## C7 0.366 32.475 -59.641 66.944 1.000 normal(0,32)
##
## Variances:
## Estimate Pri.SD pi.lower pi.upper Rhat Prior
## R1 8.535 17.649 0.003 55.898 1.000 gamma(1,.5)[sd]
## R2 8.026 20.280 0.001 54.374 0.999 gamma(1,.5)[sd]
## R3 8.612 17.897 0.003 61.040 0.999 gamma(1,.5)[sd]
## R4 8.124 17.739 0.001 60.906 0.999 gamma(1,.5)[sd]
## R5 8.139 15.714 0.004 51.213 0.999 gamma(1,.5)[sd]
## R6 8.947 22.519 0.003 56.093 0.999 gamma(1,.5)[sd]
## R7 7.520 17.669 0.002 54.187 0.999 gamma(1,.5)[sd]
## I1 8.190 18.881 0.002 57.174 0.999 gamma(1,.5)[sd]
## I2 8.159 18.177 0.000 55.028 0.999 gamma(1,.5)[sd]
## I3 8.704 18.567 0.003 59.654 1.001 gamma(1,.5)[sd]
## I4 7.774 18.312 0.002 51.355 1.002 gamma(1,.5)[sd]
## I5 7.522 18.542 0.003 45.879 1.002 gamma(1,.5)[sd]
## I6 7.164 13.477 0.005 45.915 1.002 gamma(1,.5)[sd]
## I7 7.078 14.527 0.004 47.641 1.000 gamma(1,.5)[sd]
## A1 7.188 13.600 0.008 46.291 1.001 gamma(1,.5)[sd]
## A2 7.755 16.147 0.001 55.504 1.001 gamma(1,.5)[sd]
## A3 8.363 18.676 0.003 54.900 0.999 gamma(1,.5)[sd]
## A4 7.823 19.737 0.006 45.249 1.004 gamma(1,.5)[sd]
## A5 7.786 17.474 0.003 55.168 0.999 gamma(1,.5)[sd]
## A6 8.741 18.941 0.001 64.071 1.000 gamma(1,.5)[sd]
## A7 8.200 16.246 0.002 54.536 0.999 gamma(1,.5)[sd]
## S1 8.257 19.561 0.004 51.439 1.000 gamma(1,.5)[sd]
## S2 7.954 17.083 0.003 55.716 0.999 gamma(1,.5)[sd]
## S3 8.398 21.490 0.003 57.394 1.000 gamma(1,.5)[sd]
## S4 8.334 18.600 0.003 60.066 0.999 gamma(1,.5)[sd]
## S5 7.714 15.856 0.005 51.891 1.000 gamma(1,.5)[sd]
## S6 7.968 15.380 0.005 52.879 0.999 gamma(1,.5)[sd]
## S7 7.198 14.575 0.001 50.974 0.999 gamma(1,.5)[sd]
## E1 8.505 17.390 0.002 62.816 1.000 gamma(1,.5)[sd]
## E2 7.973 19.187 0.003 55.760 1.000 gamma(1,.5)[sd]
## E3 8.882 22.676 0.004 60.104 0.999 gamma(1,.5)[sd]
## E4 8.801 19.789 0.003 60.890 0.999 gamma(1,.5)[sd]
## E5 8.251 20.723 0.006 47.443 1.005 gamma(1,.5)[sd]
## E6 7.027 14.215 0.004 48.989 1.002 gamma(1,.5)[sd]
## E7 8.395 20.776 0.001 53.668 0.999 gamma(1,.5)[sd]
## C1 8.183 16.779 0.003 57.600 1.000 gamma(1,.5)[sd]
## C2 7.392 14.839 0.007 45.609 0.999 gamma(1,.5)[sd]
## C3 7.499 15.759 0.005 42.769 0.999 gamma(1,.5)[sd]
## C4 8.388 17.352 0.005 53.300 1.000 gamma(1,.5)[sd]
## C5 6.859 16.281 0.002 46.117 0.999 gamma(1,.5)[sd]
## C6 8.131 17.076 0.002 50.283 0.999 gamma(1,.5)[sd]
## C7 9.000 19.880 0.001 62.447 0.999 gamma(1,.5)[sd]
summary(fit.2, standardized = TRUE) # Hiển thị kết quả standardized (chuẩn hóa)
## blavaan 0.5.3 ended normally after 1000 iterations
##
## Estimator BAYES
## Optimization method MCMC
## Number of model parameters 84
##
## Number of observations 1308
##
## Statistic MargLogLik PPP
## Value -132232.297 1.000
##
## Parameter Estimates:
##
##
## Intercepts:
## Estimate Pri.SD pi.lower pi.upper Std.lv Std.all
## R1 -1.063 32.628 -61.995 63.410 -1.063 -0.364
## R2 -0.657 32.964 -67.529 65.255 -0.657 -0.232
## R3 -0.424 31.757 -57.857 63.731 -0.424 -0.145
## R4 0.261 31.829 -62.359 61.608 0.261 0.092
## R5 -0.862 33.151 -67.521 63.950 -0.862 -0.302
## R6 -1.795 33.591 -70.305 62.876 -1.795 -0.600
## R7 3.514 31.499 -59.742 64.656 3.514 1.281
## I1 0.617 32.611 -62.326 65.504 0.617 0.216
## I2 0.851 33.138 -63.501 64.477 0.851 0.298
## I3 0.862 32.486 -60.564 66.650 0.862 0.292
## I4 0.462 32.095 -61.927 67.962 0.462 0.166
## I5 1.042 31.082 -59.461 61.317 1.042 0.380
## I6 1.869 31.807 -61.999 64.056 1.869 0.698
## I7 0.583 31.328 -63.555 59.255 0.583 0.219
## A1 -0.561 31.282 -63.546 60.552 -0.561 -0.209
## A2 1.474 31.074 -59.263 61.042 1.474 0.529
## A3 -0.938 31.887 -62.854 58.912 -0.938 -0.324
## A4 -0.591 33.214 -66.325 61.916 -0.591 -0.211
## A5 0.176 33.469 -62.520 63.915 0.176 0.063
## A6 -0.283 30.365 -59.096 59.322 -0.283 -0.096
## A7 -1.285 32.003 -65.366 62.010 -1.285 -0.449
## S1 0.621 33.110 -65.669 64.110 0.621 0.216
## S2 -0.196 32.211 -61.040 64.220 -0.196 -0.070
## S3 -1.554 30.332 -60.309 60.543 -1.554 -0.536
## S4 -0.145 30.706 -60.627 59.787 -0.145 -0.050
## S5 1.146 32.718 -62.937 67.499 1.146 0.413
## S6 0.077 31.651 -67.503 62.157 0.077 0.027
## S7 1.126 32.331 -64.840 65.354 1.126 0.420
## E1 -0.265 32.176 -63.177 63.260 -0.265 -0.091
## E2 0.659 32.802 -61.124 63.116 0.659 0.233
## E3 -1.358 32.115 -64.996 60.666 -1.358 -0.456
## E4 0.419 32.395 -61.457 67.093 0.419 0.141
## E5 1.937 31.448 -59.076 65.302 1.937 0.674
## E6 -0.608 31.568 -61.931 62.379 -0.608 -0.229
## E7 -0.586 32.731 -65.141 61.871 -0.586 -0.202
## C1 -0.062 33.289 -64.676 70.423 -0.062 -0.022
## C2 0.750 32.485 -62.085 60.908 0.750 0.276
## C3 0.356 30.944 -58.157 67.297 0.356 0.130
## C4 1.074 32.009 -62.279 61.186 1.074 0.371
## C5 -0.676 32.216 -64.071 65.797 -0.676 -0.258
## C6 0.479 32.658 -65.222 61.289 0.479 0.168
## C7 0.366 32.475 -59.641 66.944 0.366 0.122
## Rhat Prior
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 1.001 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 1.000 normal(0,32)
## 1.001 normal(0,32)
## 1.003 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 1.004 normal(0,32)
## 1.004 normal(0,32)
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 1.001 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 1.001 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 1.000 normal(0,32)
##
## Variances:
## Estimate Pri.SD pi.lower pi.upper Std.lv Std.all
## R1 8.535 17.649 0.003 55.898 8.535 1.000
## R2 8.026 20.280 0.001 54.374 8.026 1.000
## R3 8.612 17.897 0.003 61.040 8.612 1.000
## R4 8.124 17.739 0.001 60.906 8.124 1.000
## R5 8.139 15.714 0.004 51.213 8.139 1.000
## R6 8.947 22.519 0.003 56.093 8.947 1.000
## R7 7.520 17.669 0.002 54.187 7.520 1.000
## I1 8.190 18.881 0.002 57.174 8.190 1.000
## I2 8.159 18.177 0.000 55.028 8.159 1.000
## I3 8.704 18.567 0.003 59.654 8.704 1.000
## I4 7.774 18.312 0.002 51.355 7.774 1.000
## I5 7.522 18.542 0.003 45.879 7.522 1.000
## I6 7.164 13.477 0.005 45.915 7.164 1.000
## I7 7.078 14.527 0.004 47.641 7.078 1.000
## A1 7.188 13.600 0.008 46.291 7.188 1.000
## A2 7.755 16.147 0.001 55.504 7.755 1.000
## A3 8.363 18.676 0.003 54.900 8.363 1.000
## A4 7.823 19.737 0.006 45.249 7.823 1.000
## A5 7.786 17.474 0.003 55.168 7.786 1.000
## A6 8.741 18.941 0.001 64.071 8.741 1.000
## A7 8.200 16.246 0.002 54.536 8.200 1.000
## S1 8.257 19.561 0.004 51.439 8.257 1.000
## S2 7.954 17.083 0.003 55.716 7.954 1.000
## S3 8.398 21.490 0.003 57.394 8.398 1.000
## S4 8.334 18.600 0.003 60.066 8.334 1.000
## S5 7.714 15.856 0.005 51.891 7.714 1.000
## S6 7.968 15.380 0.005 52.879 7.968 1.000
## S7 7.198 14.575 0.001 50.974 7.198 1.000
## E1 8.505 17.390 0.002 62.816 8.505 1.000
## E2 7.973 19.187 0.003 55.760 7.973 1.000
## E3 8.882 22.676 0.004 60.104 8.882 1.000
## E4 8.801 19.789 0.003 60.890 8.801 1.000
## E5 8.251 20.723 0.006 47.443 8.251 1.000
## E6 7.027 14.215 0.004 48.989 7.027 1.000
## E7 8.395 20.776 0.001 53.668 8.395 1.000
## C1 8.183 16.779 0.003 57.600 8.183 1.000
## C2 7.392 14.839 0.007 45.609 7.392 1.000
## C3 7.499 15.759 0.005 42.769 7.499 1.000
## C4 8.388 17.352 0.005 53.300 8.388 1.000
## C5 6.859 16.281 0.002 46.117 6.859 1.000
## C6 8.131 17.076 0.002 50.283 8.131 1.000
## C7 9.000 19.880 0.001 62.447 9.000 1.000
## Rhat Prior
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.002 gamma(1,.5)[sd]
## 1.002 gamma(1,.5)[sd]
## 1.002 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.004 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.005 gamma(1,.5)[sd]
## 1.002 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
library(semPlot)
semPaths(fit.2,
whatLabels="est",
layout = "tree",
rotation = 3)
hết