Dữ liệu sử dụng trong hướng dẫn này là của PGS.TS Trần Văn Trang (Đại học Thương mại).
Bài báo gốc lấy tại: http://tckhtm.tmu.edu.vn/vi/news/cac-so-tap-chi/tap-chi-khoa-hoc-thuong-mai-so-141-153.html
Dữ liệu tải tại google diver: https://drive.google.com/drive/folders/1Npip6h8WyZjI9JGf5wonnU_scBUYj4sP?usp=sharing
setwd("D:/Tap huan VIASM/HoiThao_KHXH_2021/Projects/Y_Dinh_Hanh_Vi")
library(foreign)
require(tidyverse)
require(lavaan)
d <- read.spss("Case study Behavior Intention.sav",
use.value.label=TRUE, to.data.frame=TRUE)d1 <- d %>% select(-c("STT", "FAM", "Formation",
"Work", "Year",
"BI1", "BIRecode", "BI4"))?fa## No documentation for 'fa' in specified packages and libraries:
## you could try '??fa'Chi tiết về gói tại: https://cran.r-project.org/web/packages/lavaan/index.html
Tìm hiểu hàm cfa để ước lượng mô hình phân tích nhân tố khẳng định
? cfa## starting httpd help server ... donecfa.model1 <- ' BEINTEN =~ BI2 + BI3 + BI5 + BI6
RELA =~ REL1 + REL2 + REL4
# Covariance
BI2 ~~ BI3
REL1 ~~ REL4 '
cfa.d1 <- cfa(cfa.model1, data = d1)
summary(cfa.d1, fit.measures = TRUE)## lavaan 0.6-8 ended normally after 37 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 17
##
## Number of observations 826
##
## Model Test User Model:
##
## Test statistic 33.258
## Degrees of freedom 11
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 2068.806
## Degrees of freedom 21
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.989
## Tucker-Lewis Index (TLI) 0.979
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -9177.960
## Loglikelihood unrestricted model (H1) -9161.331
##
## Akaike (AIC) 18389.920
## Bayesian (BIC) 18470.102
## Sample-size adjusted Bayesian (BIC) 18416.116
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.049
## 90 Percent confidence interval - lower 0.031
## 90 Percent confidence interval - upper 0.069
## P-value RMSEA <= 0.05 0.482
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.024
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|)
## BEINTEN =~
## BI2 1.000
## BI3 1.054 0.064 16.361 0.000
## BI5 1.311 0.081 16.089 0.000
## BI6 1.348 0.086 15.656 0.000
## RELA =~
## REL1 1.000
## REL2 0.863 0.047 18.358 0.000
## REL4 0.582 0.041 14.305 0.000
##
## Covariances:
## Estimate Std.Err z-value P(>|z|)
## .BI2 ~~
## .BI3 0.252 0.046 5.457 0.000
## .REL1 ~~
## .REL4 -0.273 0.064 -4.233 0.000
## BEINTEN ~~
## RELA 0.746 0.064 11.690 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .BI2 0.930 0.055 16.779 0.000
## .BI3 1.141 0.067 17.071 0.000
## .BI5 0.704 0.055 12.828 0.000
## .BI6 0.998 0.068 14.720 0.000
## .REL1 0.473 0.093 5.098 0.000
## .REL2 0.987 0.080 12.346 0.000
## .REL4 1.304 0.083 15.770 0.000
## BEINTEN 0.623 0.069 9.065 0.000
## RELA 1.944 0.147 13.210 0.000#=================================================================
#2.================Quy trinh cuoi EFA=============================
#=================================================================
cfa.model2 <- ' BEINTEN =~ BI2 + BI3 + BI5 + BI6
RELA =~ REL1 + REL2 + REL3+ REL4
EDUC =~ EDU1 + EDU2 + EDU3 + EDU4 + EDU5 + EDU6 + EDU7 + EDU8
GOVE =~ GOV1 + GOV2 + GOV3 + GOV4 + GOV5
ENDO =~ END1 + END2 + END3 + END4 + END5 ' #No END1 in the Trang (2020)
cfa.d2 <- cfa(cfa.model2, data = d1)
summary(cfa.d2, fit.measures = TRUE)## lavaan 0.6-8 ended normally after 41 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 62
##
## Number of observations 826
##
## Model Test User Model:
##
## Test statistic 1483.744
## Degrees of freedom 289
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 11390.969
## Degrees of freedom 325
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.892
## Tucker-Lewis Index (TLI) 0.879
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -30645.787
## Loglikelihood unrestricted model (H1) -29903.915
##
## Akaike (AIC) 61415.574
## Bayesian (BIC) 61708.003
## Sample-size adjusted Bayesian (BIC) 61511.113
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.071
## 90 Percent confidence interval - lower 0.067
## 90 Percent confidence interval - upper 0.074
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.059
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|)
## BEINTEN =~
## BI2 1.000
## BI3 1.067 0.066 16.175 0.000
## BI5 1.199 0.067 17.822 0.000
## BI6 1.196 0.072 16.693 0.000
## RELA =~
## REL1 1.000
## REL2 1.036 0.046 22.370 0.000
## REL3 0.842 0.042 20.276 0.000
## REL4 0.719 0.042 17.221 0.000
## EDUC =~
## EDU1 1.000
## EDU2 1.013 0.047 21.351 0.000
## EDU3 1.072 0.049 21.889 0.000
## EDU4 1.093 0.051 21.231 0.000
## EDU5 0.979 0.046 21.242 0.000
## EDU6 0.964 0.053 18.246 0.000
## EDU7 1.001 0.047 21.282 0.000
## EDU8 0.860 0.045 19.124 0.000
## GOVE =~
## GOV1 1.000
## GOV2 1.101 0.053 20.609 0.000
## GOV3 1.118 0.054 20.891 0.000
## GOV4 1.054 0.054 19.600 0.000
## GOV5 0.897 0.053 17.054 0.000
## ENDO =~
## END1 1.000
## END2 1.435 0.087 16.586 0.000
## END3 1.442 0.084 17.102 0.000
## END4 1.218 0.079 15.401 0.000
## END5 1.369 0.093 14.718 0.000
##
## Covariances:
## Estimate Std.Err z-value P(>|z|)
## BEINTEN ~~
## RELA 0.687 0.059 11.558 0.000
## EDUC 0.309 0.038 8.128 0.000
## GOVE 0.264 0.034 7.811 0.000
## ENDO -0.015 0.024 -0.647 0.517
## RELA ~~
## EDUC 0.536 0.055 9.779 0.000
## GOVE 0.411 0.047 8.695 0.000
## ENDO 0.019 0.033 0.585 0.558
## EDUC ~~
## GOVE 0.448 0.041 10.837 0.000
## ENDO 0.175 0.028 6.326 0.000
## GOVE ~~
## ENDO 0.146 0.025 5.957 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .BI2 0.830 0.050 16.462 0.000
## .BI3 1.011 0.060 16.722 0.000
## .BI5 0.736 0.052 14.040 0.000
## .BI6 1.095 0.068 16.128 0.000
## .REL1 0.945 0.064 14.735 0.000
## .REL2 0.854 0.062 13.705 0.000
## .REL3 0.938 0.057 16.373 0.000
## .REL4 1.203 0.066 18.114 0.000
## .EDU1 0.932 0.050 18.660 0.000
## .EDU2 0.553 0.032 17.435 0.000
## .EDU3 0.535 0.032 16.974 0.000
## .EDU4 0.665 0.038 17.526 0.000
## .EDU5 0.532 0.030 17.517 0.000
## .EDU6 1.019 0.054 18.910 0.000
## .EDU7 0.551 0.031 17.488 0.000
## .EDU8 0.675 0.036 18.621 0.000
## .GOV1 0.774 0.043 17.946 0.000
## .GOV2 0.426 0.028 14.996 0.000
## .GOV3 0.395 0.027 14.402 0.000
## .GOV4 0.538 0.033 16.486 0.000
## .GOV5 0.735 0.040 18.315 0.000
## .END1 0.794 0.043 18.408 0.000
## .END2 0.594 0.040 14.847 0.000
## .END3 0.422 0.033 12.649 0.000
## .END4 0.715 0.042 17.125 0.000
## .END5 1.145 0.064 17.819 0.000
## BEINTEN 0.723 0.071 10.180 0.000
## RELA 1.472 0.118 12.469 0.000
## EDUC 0.899 0.080 11.230 0.000
## GOVE 0.691 0.064 10.720 0.000
## ENDO 0.445 0.050 8.859 0.000fitted(cfa.d2)## $cov
## BI2 BI3 BI5 BI6 REL1 REL2 REL3 REL4 EDU1 EDU2
## BI2 1.553
## BI3 0.771 1.833
## BI5 0.867 0.925 1.775
## BI6 0.865 0.923 1.037 2.130
## REL1 0.687 0.733 0.823 0.822 2.417
## REL2 0.712 0.759 0.853 0.851 1.525 2.434
## REL3 0.578 0.617 0.693 0.692 1.239 1.284 1.981
## REL4 0.494 0.527 0.592 0.590 1.058 1.096 0.891 1.963
## EDU1 0.309 0.330 0.370 0.370 0.536 0.555 0.451 0.385 1.831
## EDU2 0.313 0.334 0.375 0.374 0.543 0.562 0.457 0.390 0.910 1.475
## EDU3 0.331 0.353 0.397 0.396 0.575 0.595 0.484 0.413 0.964 0.976
## EDU4 0.338 0.360 0.405 0.404 0.586 0.607 0.493 0.421 0.982 0.995
## EDU5 0.303 0.323 0.363 0.362 0.525 0.544 0.442 0.377 0.880 0.892
## EDU6 0.298 0.318 0.357 0.356 0.517 0.535 0.435 0.371 0.867 0.878
## EDU7 0.310 0.330 0.371 0.370 0.537 0.556 0.452 0.386 0.900 0.912
## EDU8 0.266 0.284 0.319 0.318 0.461 0.478 0.388 0.331 0.773 0.783
## GOV1 0.264 0.282 0.317 0.316 0.411 0.426 0.346 0.296 0.448 0.454
## GOV2 0.291 0.310 0.349 0.348 0.453 0.469 0.381 0.326 0.493 0.500
## GOV3 0.295 0.315 0.354 0.353 0.460 0.477 0.387 0.331 0.501 0.507
## GOV4 0.278 0.297 0.334 0.333 0.433 0.449 0.365 0.311 0.472 0.478
## GOV5 0.237 0.253 0.284 0.283 0.369 0.382 0.311 0.265 0.402 0.407
## END1 -0.015 -0.016 -0.019 -0.018 0.019 0.020 0.016 0.014 0.175 0.177
## END2 -0.022 -0.024 -0.027 -0.027 0.028 0.029 0.024 0.020 0.251 0.254
## END3 -0.022 -0.024 -0.027 -0.027 0.028 0.029 0.024 0.020 0.252 0.255
## END4 -0.019 -0.020 -0.023 -0.022 0.024 0.025 0.020 0.017 0.213 0.216
## END5 -0.021 -0.023 -0.025 -0.025 0.027 0.028 0.022 0.019 0.239 0.243
## EDU3 EDU4 EDU5 EDU6 EDU7 EDU8 GOV1 GOV2 GOV3 GOV4
## BI2
## BI3
## BI5
## BI6
## REL1
## REL2
## REL3
## REL4
## EDU1
## EDU2
## EDU3 1.568
## EDU4 1.053 1.738
## EDU5 0.944 0.962 1.395
## EDU6 0.929 0.947 0.849 1.855
## EDU7 0.965 0.984 0.882 0.868 1.452
## EDU8 0.829 0.845 0.757 0.746 0.774 1.340
## GOV1 0.480 0.490 0.439 0.432 0.449 0.385 1.464
## GOV2 0.529 0.539 0.483 0.476 0.494 0.424 0.761 1.264
## GOV3 0.537 0.547 0.491 0.483 0.502 0.431 0.772 0.851 1.259
## GOV4 0.506 0.516 0.462 0.455 0.473 0.406 0.728 0.802 0.814 1.305
## GOV5 0.431 0.439 0.394 0.387 0.402 0.346 0.620 0.682 0.693 0.653
## END1 0.188 0.191 0.171 0.169 0.175 0.151 0.146 0.161 0.163 0.154
## END2 0.269 0.274 0.246 0.242 0.251 0.216 0.210 0.231 0.234 0.221
## END3 0.270 0.276 0.247 0.243 0.253 0.217 0.211 0.232 0.236 0.222
## END4 0.228 0.233 0.209 0.205 0.213 0.183 0.178 0.196 0.199 0.187
## END5 0.257 0.262 0.235 0.231 0.240 0.206 0.200 0.220 0.224 0.211
## GOV5 END1 END2 END3 END4 END5
## BI2
## BI3
## BI5
## BI6
## REL1
## REL2
## REL3
## REL4
## EDU1
## EDU2
## EDU3
## EDU4
## EDU5
## EDU6
## EDU7
## EDU8
## GOV1
## GOV2
## GOV3
## GOV4
## GOV5 1.291
## END1 0.131 1.239
## END2 0.188 0.639 1.511
## END3 0.189 0.642 0.921 1.348
## END4 0.160 0.542 0.778 0.782 1.376
## END5 0.179 0.610 0.875 0.879 0.742 1.979coef(cfa.d2)## BEINTEN=~BI3 BEINTEN=~BI5 BEINTEN=~BI6 RELA=~REL2
## 1.067 1.199 1.196 1.036
## RELA=~REL3 RELA=~REL4 EDUC=~EDU2 EDUC=~EDU3
## 0.842 0.719 1.013 1.072
## EDUC=~EDU4 EDUC=~EDU5 EDUC=~EDU6 EDUC=~EDU7
## 1.093 0.979 0.964 1.001
## EDUC=~EDU8 GOVE=~GOV2 GOVE=~GOV3 GOVE=~GOV4
## 0.860 1.101 1.118 1.054
## GOVE=~GOV5 ENDO=~END2 ENDO=~END3 ENDO=~END4
## 0.897 1.435 1.442 1.218
## ENDO=~END5 BI2~~BI2 BI3~~BI3 BI5~~BI5
## 1.369 0.830 1.011 0.736
## BI6~~BI6 REL1~~REL1 REL2~~REL2 REL3~~REL3
## 1.095 0.945 0.854 0.938
## REL4~~REL4 EDU1~~EDU1 EDU2~~EDU2 EDU3~~EDU3
## 1.203 0.932 0.553 0.535
## EDU4~~EDU4 EDU5~~EDU5 EDU6~~EDU6 EDU7~~EDU7
## 0.665 0.532 1.019 0.551
## EDU8~~EDU8 GOV1~~GOV1 GOV2~~GOV2 GOV3~~GOV3
## 0.675 0.774 0.426 0.395
## GOV4~~GOV4 GOV5~~GOV5 END1~~END1 END2~~END2
## 0.538 0.735 0.794 0.594
## END3~~END3 END4~~END4 END5~~END5 BEINTEN~~BEINTEN
## 0.422 0.715 1.145 0.723
## RELA~~RELA EDUC~~EDUC GOVE~~GOVE ENDO~~ENDO
## 1.472 0.899 0.691 0.445
## BEINTEN~~RELA BEINTEN~~EDUC BEINTEN~~GOVE BEINTEN~~ENDO
## 0.687 0.309 0.264 -0.015
## RELA~~EDUC RELA~~GOVE RELA~~ENDO EDUC~~GOVE
## 0.536 0.411 0.019 0.448
## EDUC~~ENDO GOVE~~ENDO
## 0.175 0.146fitMeasures(cfa.d2, fit.measures = "all")## npar fmin chisq df
## 62.000 0.898 1483.744 289.000
## pvalue baseline.chisq baseline.df baseline.pvalue
## 0.000 11390.969 325.000 0.000
## cfi tli nnfi rfi
## 0.892 0.879 0.879 0.854
## nfi pnfi ifi rni
## 0.870 0.773 0.892 0.892
## logl unrestricted.logl aic bic
## -30645.787 -29903.915 61415.574 61708.003
## ntotal bic2 rmsea rmsea.ci.lower
## 826.000 61511.113 0.071 0.067
## rmsea.ci.upper rmsea.pvalue rmr rmr_nomean
## 0.074 0.000 0.096 0.096
## srmr srmr_bentler srmr_bentler_nomean crmr
## 0.059 0.059 0.059 0.061
## crmr_nomean srmr_mplus srmr_mplus_nomean cn_05
## 0.061 0.059 0.059 184.515
## cn_01 gfi agfi pgfi
## 194.649 0.865 0.836 0.712
## mfi ecvi
## 0.485 1.946fitMeasures(cfa.d2, c("chisq", "df", "pvalue", "gfi","cfi","tli", "rmsea"))## chisq df pvalue gfi cfi tli rmsea
## 1483.744 289.000 0.000 0.865 0.892 0.879 0.071fitMeasures(cfa.d2, c("chisq")) / fitMeasures(cfa.d2, c("df"))## chisq
## 5.134Mô hình trên cần các điều chỉnh để tăng sự phù hợp, mời các bạn theo dõi video tiếp theo. Trân trọng