R Markdown Notebook for PRFQ CFA and Measurement Invariance.
PRFQCFA.model <- 'PM =~ PRFQ1 + PRFQ4 + PRFQ7 + PRFQ10 + PRFQ13 + PRFQ16
CMS =~ PRFQ15 + PRFQ12 + PRFQ9 + PRFQ6 + PRFQ3
IC =~ PRFQ17 + PRFQ14 + PRFQ8 + PRFQ5 + PRFQ2
PRFQ6~~PRFQ9'
fit <- cfa(PRFQCFA.model, data = TrimmedfullPRFQforRandOmegacalsandR)
summary(fit, fit.measures = TRUE)lavaan (0.5-23.1097) converged normally after 42 iterations
Number of observations 317
Estimator ML
Minimum Function Test Statistic 304.047
Degrees of freedom 100
P-value (Chi-square) 0.000
Model test baseline model:
Minimum Function Test Statistic 2794.355
Degrees of freedom 120
P-value 0.000
User model versus baseline model:
Comparative Fit Index (CFI) 0.924
Tucker-Lewis Index (TLI) 0.908
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -8344.176
Loglikelihood unrestricted model (H1) -8192.153
Number of free parameters 36
Akaike (AIC) 16760.353
Bayesian (BIC) 16895.673
Sample-size adjusted Bayesian (BIC) 16781.490
Root Mean Square Error of Approximation:
RMSEA 0.080
90 Percent Confidence Interval 0.070 0.091
P-value RMSEA <= 0.05 0.000
Standardized Root Mean Square Residual:
SRMR 0.077
Parameter Estimates:
Information Expected
Standard Errors Standard
Latent Variables:
Estimate Std.Err z-value P(>|z|)
PM =~
PRFQ1 1.000
PRFQ4 1.293 0.113 11.493 0.000
PRFQ7 0.965 0.101 9.519 0.000
PRFQ10 1.360 0.115 11.794 0.000
PRFQ13 1.309 0.114 11.487 0.000
PRFQ16 1.171 0.108 10.854 0.000
CMS =~
PRFQ15 1.000
PRFQ12 1.038 0.063 16.412 0.000
PRFQ9 0.803 0.068 11.832 0.000
PRFQ6 0.620 0.075 8.241 0.000
PRFQ3 0.944 0.061 15.428 0.000
IC =~
PRFQ17 1.000
PRFQ14 0.828 0.073 11.324 0.000
PRFQ8 1.002 0.072 13.997 0.000
PRFQ5 1.056 0.078 13.448 0.000
PRFQ2 0.935 0.066 14.160 0.000
Covariances:
Estimate Std.Err z-value P(>|z|)
.PRFQ9 ~~
.PRFQ6 0.577 0.093 6.225 0.000
PM ~~
CMS -0.345 0.089 -3.872 0.000
IC 0.522 0.104 4.993 0.000
CMS ~~
IC 0.500 0.098 5.114 0.000
Variances:
Estimate Std.Err z-value P(>|z|)
.PRFQ1 2.186 0.185 11.803 0.000
.PRFQ4 1.075 0.109 9.856 0.000
.PRFQ7 1.846 0.157 11.721 0.000
.PRFQ10 0.901 0.100 8.980 0.000
.PRFQ13 1.107 0.112 9.869 0.000
.PRFQ16 1.373 0.127 10.852 0.000
.PRFQ15 0.630 0.070 9.010 0.000
.PRFQ12 0.523 0.066 7.963 0.000
.PRFQ9 1.150 0.101 11.368 0.000
.PRFQ6 1.712 0.142 12.076 0.000
.PRFQ3 0.630 0.067 9.413 0.000
.PRFQ17 0.973 0.100 9.778 0.000
.PRFQ14 1.473 0.130 11.333 0.000
.PRFQ8 0.991 0.101 9.817 0.000
.PRFQ5 1.310 0.128 10.270 0.000
.PRFQ2 0.816 0.085 9.658 0.000
PM 1.331 0.228 5.834 0.000
CMS 1.272 0.151 8.441 0.000
IC 1.510 0.192 7.865 0.000Invariance Tests.
measurementInvariance(PRFQCFA.model, data = TrimmedfullPRFQforRandOmegacalsandR, group = "Female1Male2", strict = TRUE)lavaan WARNING: group variable <U+393C><U+3E31>Female1Male2<U+393C><U+3E32> contains missing values
lavaan WARNING: group variable <U+393C><U+3E31>Female1Male2<U+393C><U+3E32> contains missing values
lavaan WARNING: group variable <U+393C><U+3E31>Female1Male2<U+393C><U+3E32> contains missing values
lavaan WARNING: group variable <U+393C><U+3E31>Female1Male2<U+393C><U+3E32> contains missing values
lavaan WARNING: group variable <U+393C><U+3E31>Female1Male2<U+393C><U+3E32> contains missing values
Measurement invariance models:
Model 1 : fit.configural
Model 2 : fit.loadings
Model 3 : fit.intercepts
Model 4 : fit.residuals
Model 5 : fit.means
Chi Square Difference Test
Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
fit.configural 200 16248 16635 438.48
fit.loadings 213 16230 16569 446.96 8.4804 13 0.8109609
fit.intercepts 226 16216 16506 458.83 11.8696 13 0.5383647
fit.residuals 242 16204 16435 479.05 20.2133 16 0.2107653
fit.means 245 16218 16438 499.29 20.2398 3 0.0001514 ***
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Fit measures:
cfi rmsea cfi.delta rmsea.delta
fit.configural 0.907 0.088 NA NA
fit.loadings 0.909 0.085 0.002 0.004
fit.intercepts 0.909 0.082 0.000 0.003
fit.residuals 0.908 0.080 0.002 0.002
fit.means 0.901 0.082 0.007 0.002