> dwc <-"ctrll =~ income+contract+skill+njob + ctrll ~ tedu01+ hleadera + ahtedua + foodr10 + tedu01 ~ ahtedua + foodr10 + " > fit.dwc <- sem(dwc,data = mplusdata,std.lv = TRUE,ordered=c("njob","contract","skill")) > summary(fit.dwc,fit.measures=TRUE,standardized=TRUE,rsquare=TRUE) lavaan 0.6-2 ended normally after 62 iterations Optimization method NLMINB Number of free parameters 20 Number of observations 5038 Estimator DWLS Robust Model Fit Test Statistic 204.197 255.715 Degrees of freedom 15 15 P-value (Chi-square) 0.000 0.000 Scaling correction factor 0.802 Shift parameter 0.997 for simple second-order correction (Mplus variant) Model test baseline model: Minimum Function Test Statistic 14641.593 12066.019 Degrees of freedom 25 25 P-value 0.000 0.000 User model versus baseline model: Comparative Fit Index (CFI) 0.987 0.980 Tucker-Lewis Index (TLI) 0.978 0.967 Robust Comparative Fit Index (CFI) NA Robust Tucker-Lewis Index (TLI) NA Root Mean Square Error of Approximation: RMSEA 0.050 0.056 90 Percent Confidence Interval 0.044 0.056 0.050 0.063 P-value RMSEA <= 0.05 0.482 0.038 Robust RMSEA NA 90 Percent Confidence Interval NA NA Standardized Root Mean Square Residual: SRMR 0.045 0.045 Parameter Estimates: Information Expected Information saturated (h1) model Unstructured Standard Errors Robust.sem Latent Variables: Estimate Std.Err z-value P(>|z|) Std.lv Std.all ctrll =~ income 0.190 0.004 48.958 0.000 0.308 0.565 contract 0.595 0.011 54.938 0.000 0.964 0.833 skill 0.653 0.010 64.789 0.000 1.060 0.892 njob -0.278 0.012 -23.019 0.000 -0.451 -0.435 Regressions: Estimate Std.Err z-value P(>|z|) Std.lv Std.all ctrll ~ tedu01 2.408 0.057 42.086 0.000 1.484 0.652 hleadera 0.715 0.131 5.469 0.000 0.441 0.060 ahtedua 0.656 0.061 10.768 0.000 0.404 0.154 foodr10 -0.096 0.015 -6.292 0.000 -0.059 -0.073 tedu01 ~ ahtedua 0.709 0.015 47.030 0.000 0.709 0.613 foodr10 -0.033 0.004 -8.278 0.000 -0.033 -0.093 Intercepts: Estimate Std.Err z-value P(>|z|) Std.lv Std.all .income 0.477 0.035 13.794 0.000 0.477 0.873 .contract 0.000 0.000 0.000 .skill 0.000 0.000 0.000 .njob 0.000 0.000 0.000 .tedu01 0.559 0.025 22.170 0.000 0.559 1.273 .ctrll 0.000 0.000 0.000 Thresholds: Estimate Std.Err z-value P(>|z|) Std.lv Std.all contract|t1 1.611 0.092 17.526 0.000 1.611 1.391 skill|t1 1.055 0.075 14.112 0.000 1.055 0.888 skill|t2 2.797 0.078 36.046 0.000 2.797 2.354 skill|t3 3.125 0.079 39.517 0.000 3.125 2.629 njob|t1 -0.592 0.098 -6.074 0.000 -0.592 -0.571 njob|t2 1.085 0.103 10.579 0.000 1.085 1.047 Variances: Estimate Std.Err z-value P(>|z|) Std.lv Std.all .income 0.203 0.003 76.961 0.000 0.203 0.681 .contract 0.411 0.411 0.307 .skill 0.289 0.289 0.205 .njob 0.871 0.871 0.810 .tedu01 0.115 0.002 49.923 0.000 0.115 0.595 .ctrll 1.000 0.380 0.380 Scales y*: Estimate Std.Err z-value P(>|z|) Std.lv Std.all contract 1.000 1.000 1.000 skill 1.000 1.000 1.000 njob 1.000 1.000 1.000 R-Square: Estimate income 0.319 contract 0.693 skill 0.795 njob 0.190 tedu01 0.405 ctrll 0.620 > fitMeasures(fit.dwc) npar fmin chisq 20.000 0.020 204.197 df pvalue chisq.scaled 15.000 0.000 255.715 df.scaled pvalue.scaled chisq.scaling.factor 15.000 0.000 0.802 baseline.chisq baseline.df baseline.pvalue 14641.593 25.000 0.000 baseline.chisq.scaled baseline.df.scaled baseline.pvalue.scaled 12066.019 25.000 0.000 baseline.chisq.scaling.factor cfi tli 1.214 0.987 0.978 nnfi rfi nfi 0.978 0.977 0.986 pnfi ifi rni 0.592 0.987 0.987 cfi.scaled tli.scaled cfi.robust 0.980 0.967 NA tli.robust nnfi.scaled nnfi.robust NA 0.967 NA rfi.scaled nfi.scaled ifi.scaled 0.965 0.979 0.979 rni.scaled rni.robust rmsea 0.980 NA 0.050 rmsea.ci.lower rmsea.ci.upper rmsea.pvalue 0.044 0.056 0.482 rmsea.scaled rmsea.ci.lower.scaled rmsea.ci.upper.scaled 0.056 0.050 0.063 rmsea.pvalue.scaled rmsea.robust rmsea.ci.lower.robust 0.038 NA NA rmsea.ci.upper.robust rmsea.pvalue.robust rmr NA NA 0.280 rmr_nomean srmr srmr_bentler 0.035 0.045 0.281 srmr_bentler_nomean srmr_bollen srmr_bollen_nomean 0.045 0.281 0.045 srmr_mplus srmr_mplus_nomean cn_05 0.281 0.045 617.579 cn_01 gfi agfi 755.275 0.993 0.985 pgfi mfi 0.426 0.981