用R进行BiFactor验证性因素分析
来自OBHRM百科
示意图
脚本与注释
library(lavaan) # 调用lavaan包，如果没有安装，需要先安装
cfadata <- read.table("http://www.statmodel.com/usersguide/chap5/ex5.6.dat") # 从Mplus官网读数据到cfadata，cfadata是自己命名，可随便定。如网速慢，可下载到本地再读取。
names(cfadata) <-c(paste("y", 1:12, sep="")) # 给变量命名
bifactormodel <- ' f1 =~ y1 +y2 +y3 # 设置模型，bifactormodel还是自己命名
f2 =~ y4 +y5 +y6
f3 =~ y7 +y8 +y9
f4 =~ y10 +y11 +y12
G =~ y1 +y2 +y3+y4 +y5 +y6 +y7 +y8 +y9 +y10 +y11 +y12 '
bifactorfit <- cfa(bifactormodel, cfadata,orthogonal=TRUE) # 进行CFA，必须加上orthogonal=TRUE，bifactorfit为自己命名，方便后面调用
summary(bifactorfit,fit.measures="TRUE") # 显示总体结果
fitMeasures(bifactorfit,fit.measures="all", baseline.model=NULL) # 显示所有拟合指数
standardizedSolution(bifactorfit) # 显示标准化的结果
library(semTools) # 调用semTools包，如果没有安装，需要先安装
reliability(bifactorfit) # 计算AVE、CR（Composite Reliability）等值
library(semPlot) # 调用semPlot包，如果没有安装，需要先安装
semPaths(bifactorfit, bifactor = "G",
title=F, what = "std", residuals = FALSE,
intercepts = FALSE, layout = "tree2",
label.cex=1, edge.label.cex=0.9, font=2,
edge.color="black", fixedStyle = c("black",1),freeStyle = c("black",1),esize = 0.01,
rotation=1) # 画图,bifactor指定哪个因素为bifactor；rotation控制方向，取值为1/2/3/4
结果
总体结果
> summary(bifactorfit,fit.measures="TRUE")
lavaan 0.6-4 ended normally after 49 iterations
Optimization method NLMINB
Number of free parameters 36
Number of observations 500
Estimator ML
Model Fit Test Statistic 41.640
Degrees of freedom 42
P-value (Chi-square) 0.487
Model test baseline model:
Minimum Function Test Statistic 4012.035
Degrees of freedom 66
P-value 0.000
User model versus baseline model:
Comparative Fit Index (CFI) 1.000
Tucker-Lewis Index (TLI) 1.000
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -7208.821
Loglikelihood unrestricted model (H1) -7188.001
Number of free parameters 36
Akaike (AIC) 14489.643
Bayesian (BIC) 14641.369
Sample-size adjusted Bayesian (BIC) 14527.102
Root Mean Square Error of Approximation:
RMSEA 0.000
90 Percent Confidence Interval 0.000 0.030
P-value RMSEA <= 0.05 1.000
Standardized Root Mean Square Residual:
SRMR 0.018
Parameter Estimates:
Information Expected
Information saturated (h1) model Structured
Standard Errors Standard
Latent Variables:
Estimate Std.Err z-value P(>|z|)
f1 =~
y1 1.000
y2 0.784 0.047 16.668 0.000
y3 0.726 0.048 15.196 0.000
f2 =~
y4 1.000
y5 0.738 0.042 17.660 0.000
y6 0.712 0.042 17.027 0.000
f3 =~
y7 1.000
y8 0.720 0.046 15.792 0.000
y9 0.675 0.042 15.919 0.000
f4 =~
y10 1.000
y11 0.748 0.038 19.918 0.000
y12 0.656 0.035 18.671 0.000
G =~
y1 1.000
y2 0.728 0.057 12.865 0.000
y3 0.584 0.057 10.233 0.000
y4 0.898 0.141 6.361 0.000
y5 0.613 0.102 5.996 0.000
y6 0.621 0.104 5.983 0.000
y7 1.132 0.170 6.646 0.000
y8 0.769 0.122 6.281 0.000
y9 0.809 0.124 6.503 0.000
y10 0.803 0.136 5.886 0.000
y11 0.581 0.103 5.661 0.000
y12 0.573 0.099 5.797 0.000
Covariances:
Estimate Std.Err z-value P(>|z|)
f1 ~~
f2 0.000
f3 0.000
f4 0.000
G 0.000
f2 ~~
f3 0.000
f4 0.000
G 0.000
f3 ~~
f4 0.000
G 0.000
f4 ~~
G 0.000
Variances:
Estimate Std.Err z-value P(>|z|)
.y1 0.358 0.042 8.584 0.000
.y2 0.249 0.026 9.411 0.000
.y3 0.310 0.027 11.443 0.000
.y4 0.374 0.045 8.287 0.000
.y5 0.262 0.027 9.810 0.000
.y6 0.329 0.028 11.561 0.000
.y7 0.273 0.040 6.864 0.000
.y8 0.279 0.026 10.830 0.000
.y9 0.277 0.024 11.518 0.000
.y10 0.363 0.046 7.878 0.000
.y11 0.263 0.028 9.426 0.000
.y12 0.324 0.027 12.080 0.000
f1 0.857 0.109 7.884 0.000
f2 1.029 0.114 9.056 0.000
f3 0.962 0.126 7.624 0.000
f4 1.221 0.120 10.133 0.000
G 0.511 0.108 4.745 0.000
拟合指数
> fitMeasures(bifactorfit,fit.measures="all", baseline.model=NULL) # 显示所有拟合指数
npar fmin chisq
36.000 0.042 41.640
df pvalue baseline.chisq
42.000 0.487 4012.035
baseline.df baseline.pvalue cfi
66.000 0.000 1.000
tli nnfi rfi
1.000 1.000 0.984
nfi pnfi ifi
0.990 0.630 1.000
rni logl unrestricted.logl
1.000 -7208.821 -7188.001
aic bic ntotal
14489.643 14641.369 500.000
bic2 rmsea rmsea.ci.lower
14527.102 0.000 0.000
rmsea.ci.upper rmsea.pvalue rmr
0.030 1.000 0.021
rmr_nomean srmr srmr_bentler
0.021 0.018 0.018
srmr_bentler_nomean crmr crmr_nomean
0.018 0.019 0.019
srmr_mplus srmr_mplus_nomean cn_05
0.018 0.018 698.938
cn_01 gfi agfi
795.987 0.986 0.975
pgfi mfi ecvi
0.531 1.000 0.227
标准化的结果
> standardizedSolution(bifactorfit) lhs op rhs est.std se z pvalue ci.lower ci.upper 1 f1 =~ y1 0.705 0.040 17.680 0 0.627 0.783 2 f1 =~ y2 0.710 0.039 18.248 0 0.633 0.786 3 f1 =~ y3 0.695 0.038 18.337 0 0.621 0.769 4 f2 =~ y4 0.753 0.034 21.874 0 0.685 0.820 5 f2 =~ y5 0.743 0.034 22.002 0 0.677 0.809 6 f2 =~ y6 0.705 0.035 20.239 0 0.637 0.774 7 f3 =~ y7 0.714 0.043 16.429 0 0.628 0.799 8 f3 =~ y8 0.680 0.043 15.816 0 0.596 0.764 9 f3 =~ y9 0.646 0.045 14.378 0 0.558 0.734 10 f4 =~ y10 0.799 0.030 26.731 0 0.740 0.857 11 f4 =~ y11 0.782 0.030 26.213 0 0.723 0.840 12 f4 =~ y12 0.719 0.032 22.542 0 0.656 0.781 13 G =~ y1 0.544 0.051 10.724 0 0.445 0.643 14 G =~ y2 0.508 0.052 9.789 0 0.407 0.610 15 G =~ y3 0.431 0.054 7.942 0 0.325 0.538 16 G =~ y4 0.476 0.051 9.339 0 0.376 0.576 17 G =~ y5 0.435 0.052 8.307 0 0.332 0.538 18 G =~ y6 0.434 0.052 8.274 0 0.331 0.536 19 G =~ y7 0.588 0.051 11.460 0 0.488 0.689 20 G =~ y8 0.529 0.053 9.907 0 0.424 0.634 21 G =~ y9 0.564 0.052 10.804 0 0.462 0.666 22 G =~ y10 0.415 0.052 7.972 0 0.313 0.517 23 G =~ y11 0.392 0.053 7.444 0 0.289 0.496 24 G =~ y12 0.406 0.052 7.758 0 0.303 0.508 25 y1 ~~ y1 0.207 0.026 7.927 0 0.156 0.259 26 y2 ~~ y2 0.238 0.028 8.642 0 0.184 0.292 27 y3 ~~ y3 0.331 0.031 10.548 0 0.270 0.393 28 y4 ~~ y4 0.206 0.027 7.689 0 0.154 0.259 29 y5 ~~ y5 0.258 0.029 9.008 0 0.202 0.315 30 y6 ~~ y6 0.315 0.030 10.561 0 0.256 0.373 31 y7 ~~ y7 0.145 0.022 6.445 0 0.101 0.188 32 y8 ~~ y8 0.258 0.026 9.777 0 0.206 0.310 33 y9 ~~ y9 0.264 0.026 10.301 0 0.214 0.314 34 y10 ~~ y10 0.190 0.026 7.333 0 0.139 0.241 35 y11 ~~ y11 0.235 0.027 8.647 0 0.182 0.288 36 y12 ~~ y12 0.318 0.029 10.973 0 0.262 0.375 37 f1 ~~ f1 1.000 0.000 NA NA 1.000 1.000 38 f2 ~~ f2 1.000 0.000 NA NA 1.000 1.000 39 f3 ~~ f3 1.000 0.000 NA NA 1.000 1.000 40 f4 ~~ f4 1.000 0.000 NA NA 1.000 1.000 41 G ~~ G 1.000 0.000 NA NA 1.000 1.000 42 f1 ~~ f2 0.000 0.000 NA NA 0.000 0.000 43 f1 ~~ f3 0.000 0.000 NA NA 0.000 0.000 44 f1 ~~ f4 0.000 0.000 NA NA 0.000 0.000 45 f1 ~~ G 0.000 0.000 NA NA 0.000 0.000 46 f2 ~~ f3 0.000 0.000 NA NA 0.000 0.000 47 f2 ~~ f4 0.000 0.000 NA NA 0.000 0.000 48 f2 ~~ G 0.000 0.000 NA NA 0.000 0.000 49 f3 ~~ f4 0.000 0.000 NA NA 0.000 0.000 50 f3 ~~ G 0.000 0.000 NA NA 0.000 0.000 51 f4 ~~ G 0.000 0.000 NA NA 0.000 0.000
自动生成的结果图
