Report
Examples
model='LATENT=~ITEM1+ITEM2+ITEM3+ITEM4+ITEM5'
df<-lavaan::simulateData(model=model,model.type="cfa",
return.type="data.frame",sample.nobs=100)
df<-generate_missing(df)
fit<-lavaan::cfa(model,data=df,missing="ML")
report_cfa(fit)
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.labels' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.class' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'list.by.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'drop.list.single.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.labels' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.class' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'list.by.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'drop.list.single.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.labels' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.class' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'list.by.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'drop.list.single.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.labels' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.class' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'list.by.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'drop.list.single.group' for 'inspect'
#> Skipping circle_parameters_wih_equality_constraints: replacement has 0 rows, data has 5
#> Skipping tree_parameters_wih_equality_constraints: replacement has 0 rows, data has 5
#> Skipping spring_parameters_wih_equality_constraints: replacement has 0 rows, data has 5
#> [1] "##################################################"
#> [1] "SUMMARY"
#> [1] "##################################################"
#> lavaan 0.7-3 ended normally after 26 iterations
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 15
#>
#> Number of observations 100
#> Number of missing patterns 8
#>
#> Model Test User Model:
#>
#> Test statistic 0.674
#> Degrees of freedom 5
#> P-value (Chi-square) 0.984
#>
#> Browne's residual (NT model-based) test
#> Test statistic 1.993
#> Degrees of freedom 5
#> P-value (Chi-square) 0.850
#>
#> Model Test Baseline Model:
#>
#> Test statistic 174.479
#> Degrees of freedom 10
#> P-value 0.000
#>
#> User Model versus Baseline Model:
#>
#> Comparative Fit Index (CFI) 1.000
#> Tucker-Lewis Index (TLI) 1.053
#>
#> Robust Comparative Fit Index (CFI) 1.000
#> Robust Tucker-Lewis Index (TLI) 1.055
#>
#> Loglikelihood and Information Criteria:
#>
#> Loglikelihood user model (H0) -749.132
#> Loglikelihood unrestricted model (H1) -748.795
#>
#> Akaike (AIC) 1528.264
#> Bayesian (BIC) 1567.341
#> Sample-size adjusted Bayesian (SABIC) 1519.967
#>
#> Root Mean Square Error of Approximation:
#>
#> RMSEA 0.000
#> 90 Percent confidence interval - lower 0.000
#> 90 Percent confidence interval - upper 0.000
#> P-value H_0: RMSEA <= 0.050 0.991
#> P-value H_0: RMSEA >= 0.080 0.004
#>
#> Robust RMSEA 0.000
#> 90 Percent confidence interval - lower 0.000
#> 90 Percent confidence interval - upper 0.000
#> P-value H_0: Robust RMSEA <= 0.050 0.989
#> P-value H_0: Robust RMSEA >= 0.080 0.005
#>
#> Standardized Root Mean Square Residual:
#>
#> SRMR 0.010
#>
#> Goodness of Fit Index:
#>
#> Goodness of Fit Index (GFI) 1.000
#> 90 Percent confidence interval - lower 1.000
#> 90 Percent confidence interval - upper 1.000
#>
#> Robust GFI 1.000
#> 90 Percent confidence interval - lower 1.000
#> 90 Percent confidence interval - upper 1.000
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Observed
#> Observed information based on Hessian
#>
#> Latent Variables:
#> Estimate Std.Err z-value P(>|z|) Std.lv Std.all
#> LATENT =~
#> ITEM1 1.000 1.116 0.704
#> ITEM2 0.894 0.145 6.165 0.000 0.998 0.716
#> ITEM3 1.075 0.158 6.786 0.000 1.200 0.815
#> ITEM4 0.820 0.140 5.875 0.000 0.915 0.691
#> ITEM5 0.781 0.132 5.911 0.000 0.872 0.688
#>
#> Intercepts:
#> Estimate Std.Err z-value P(>|z|) Std.lv Std.all
#> .ITEM1 -0.053 0.161 -0.332 0.740 -0.053 -0.034
#> .ITEM2 -0.207 0.142 -1.458 0.145 -0.207 -0.148
#> .ITEM3 -0.139 0.149 -0.931 0.352 -0.139 -0.094
#> .ITEM4 -0.088 0.134 -0.656 0.512 -0.088 -0.067
#> .ITEM5 -0.265 0.129 -2.058 0.040 -0.265 -0.209
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|) Std.lv Std.all
#> .ITEM1 1.267 0.226 5.612 0.000 1.267 0.504
#> .ITEM2 0.949 0.171 5.553 0.000 0.949 0.488
#> .ITEM3 0.728 0.167 4.351 0.000 0.728 0.336
#> .ITEM4 0.915 0.160 5.723 0.000 0.915 0.522
#> .ITEM5 0.846 0.147 5.753 0.000 0.846 0.526
#> LATENT 1.246 0.338 3.688 0.000 1.000 1.000
#>
#> R-Square:
#> Estimate
#> ITEM1 0.496
#> ITEM2 0.512
#> ITEM3 0.664
#> ITEM4 0.478
#> ITEM5 0.474
#>
#> [1] "##################################################"
#> [1] "R_SQUARED"
#> [1] "##################################################"
#> r_squared
#> ITEM1 0.4960
#> ITEM2 0.5121
#> ITEM3 0.6642
#> ITEM4 0.4778
#> ITEM5 0.4737
#> [1] "##################################################"
#> [1] "FIT INDICES"
#> [1] "##################################################"
#> fit
#> npar 15.000000
#> fmin 0.003370
#> chisq 0.674046
#> df 5.000000
#> pvalue 0.984363
#> baseline.chisq 174.478659
#> baseline.df 10.000000
#> baseline.pvalue 0.000000
#> cfi 1.000000
#> tli 1.052602
#> cfi.robust 1.000000
#> tli.robust 1.055065
#> nnfi 1.052602
#> rfi 0.992274
#> nfi 0.996137
#> pnfi 0.498068
#> ifi 1.025525
#> rni 1.026301
#> nnfi.robust 1.055065
#> rni.robust 1.027533
#> logl -749.131822
#> unrestricted.logl -748.794799
#> aic 1528.263645
#> bic 1567.341197
#> ntotal 100.000000
#> bic2 1519.967429
#> rmsea 0.000000
#> rmsea.ci.lower 0.000000
#> rmsea.ci.upper 0.000000
#> rmsea.ci.level 0.900000
#> rmsea.pvalue 0.991126
#> rmsea.close.h0 0.050000
#> rmsea.notclose.pvalue 0.003662
#> rmsea.notclose.h0 0.080000
#> rmsea.robust 0.000000
#> rmsea.ci.lower.robust 0.000000
#> rmsea.ci.upper.robust 0.000000
#> rmsea.pvalue.robust 0.989151
#> rmsea.notclose.pvalue.robust 0.004981
#> rmr 0.019733
#> rmr_nomean 0.022770
#> srmr 0.010002
#> srmr_bentler 0.010002
#> srmr_bentler_nomean 0.011538
#> crmr 0.011490
#> crmr_nomean 0.014058
#> srmr_mplus 0.010000
#> srmr_mplus_nomean 0.011535
#> gfi 1.000000
#> gfi.ci.lower 1.000000
#> gfi.ci.upper 1.000000
#> gfi.ci.level 0.900000
#> gfi.robust 1.000000
#> gfi.ci.lower.robust 1.000000
#> gfi.ci.upper.robust 1.000000
#> cn_05 1643.395407
#> cn_01 2239.167181
#> gfi_lisrel 0.990266
#> agfi_lisrel 0.961064
#> pgfi 0.247566
#> mfi 1.021865
#> ecvi 0.306740
#> [1] "##################################################"
#> [1] "PARAMETERS"
#> [1] "##################################################"
#> lhs op rhs exo est se z pvalue ci.lower ci.upper std.lv std.all
#> 1 LATENT =~ ITEM1 0 1.00000 0.0000 NA NA 1.0000 1.00000 1.11643 0.70424
#> 2 LATENT =~ ITEM2 0 0.89419 0.1451 6.1647 0.00000000070625 0.6099 1.17848 0.99829 0.71562
#> 3 LATENT =~ ITEM3 0 1.07504 0.1584 6.7855 0.00000000001157 0.7645 1.38555 1.20020 0.81498
#> 4 LATENT =~ ITEM4 0 0.81956 0.1395 5.8746 0.00000000423789 0.5461 1.09299 0.91498 0.69123
#> 5 LATENT =~ ITEM5 0 0.78140 0.1322 5.9106 0.00000000340802 0.5223 1.04051 0.87237 0.68825
#> 6 ITEM1 ~~ ITEM1 0 1.26674 0.2257 5.6124 0.00000001995429 0.8244 1.70911 1.26674 0.50405
#> 7 ITEM2 ~~ ITEM2 0 0.94947 0.1710 5.5531 0.00000002806169 0.6144 1.28458 0.94947 0.48789
#> 8 ITEM3 ~~ ITEM3 0 0.72828 0.1674 4.3510 0.00001355217445 0.4002 1.05634 0.72828 0.33581
#> 9 ITEM4 ~~ ITEM4 0 0.91499 0.1599 5.7229 0.00000001047405 0.6016 1.22836 0.91499 0.52220
#> 10 ITEM5 ~~ ITEM5 0 0.84560 0.1470 5.7529 0.00000000877034 0.5575 1.13368 0.84560 0.52632
#> 11 LATENT ~~ LATENT 0 1.24641 0.3379 3.6884 0.00022571087869 0.5841 1.90874 1.00000 1.00000
#> 12 ITEM1 ~1 0 -0.05338 0.1610 -0.3316 0.74021280963860 -0.3689 0.26217 -0.05338 -0.03367
#> 13 ITEM2 ~1 0 -0.20653 0.1417 -1.4580 0.14484703309578 -0.4842 0.07111 -0.20653 -0.14805
#> 14 ITEM3 ~1 0 -0.13891 0.1492 -0.9313 0.35170464156875 -0.4312 0.15343 -0.13891 -0.09432
#> 15 ITEM4 ~1 0 -0.08822 0.1345 -0.6561 0.51177311709724 -0.3518 0.17533 -0.08822 -0.06665
#> 16 ITEM5 ~1 0 -0.26501 0.1288 -2.0580 0.03958868413543 -0.5174 -0.01263 -0.26501 -0.20908
#> 17 LATENT ~1 0 0.00000 0.0000 NA NA 0.0000 0.00000 0.00000 0.00000
#> 18 ITEM1 r2 ITEM1 0 0.49595 NA NA NA NA NA NA NA
#> 19 ITEM2 r2 ITEM2 0 0.51211 NA NA NA NA NA NA NA
#> 20 ITEM3 r2 ITEM3 0 0.66419 NA NA NA NA NA NA NA
#> 21 ITEM4 r2 ITEM4 0 0.47780 NA NA NA NA NA NA NA
#> 22 ITEM5 r2 ITEM5 0 0.47368 NA NA NA NA NA NA NA
#> [1] "##################################################"
#> [1] "UNSTANDARDIZED PARAMETERS"
#> [1] "##################################################"
#> $lambda
#> LATENT
#> ITEM1 1.000
#> ITEM2 0.894
#> ITEM3 1.075
#> ITEM4 0.820
#> ITEM5 0.781
#>
#> $theta
#> ITEM1 ITEM2 ITEM3 ITEM4 ITEM5
#> ITEM1 1.267
#> ITEM2 0.000 0.949
#> ITEM3 0.000 0.000 0.728
#> ITEM4 0.000 0.000 0.000 0.915
#> ITEM5 0.000 0.000 0.000 0.000 0.846
#>
#> $psi
#> LATENT
#> LATENT 1.246
#>
#> $nu
#> intrcp
#> ITEM1 -0.053
#> ITEM2 -0.207
#> ITEM3 -0.139
#> ITEM4 -0.088
#> ITEM5 -0.265
#>
#> $alpha
#> intrcp
#> LATENT 0
#>
#> [1] "##################################################"
#> [1] "STANDARDIZED PARAMETERS"
#> [1] "##################################################"
#> $lambda
#> LATENT
#> ITEM1 0.704
#> ITEM2 0.716
#> ITEM3 0.815
#> ITEM4 0.691
#> ITEM5 0.688
#>
#> $theta
#> ITEM1 ITEM2 ITEM3 ITEM4 ITEM5
#> ITEM1 0.504
#> ITEM2 0.000 0.488
#> ITEM3 0.000 0.000 0.336
#> ITEM4 0.000 0.000 0.000 0.522
#> ITEM5 0.000 0.000 0.000 0.000 0.526
#>
#> $psi
#> LATENT
#> LATENT 1
#>
#> $nu
#> intrcp
#> ITEM1 -0.034
#> ITEM2 -0.148
#> ITEM3 -0.094
#> ITEM4 -0.067
#> ITEM5 -0.209
#>
#> $alpha
#> intrcp
#> LATENT 0
#>
#> [1] "##################################################"
#> [1] "SAMPLE COVARIANCE"
#> [1] "##################################################"
#> X1 X2 X3 X4 X5
#> 1 2.526 1.1726 1.355 1.0057 1.0740
#> 2 1.173 1.9700 1.226 0.9421 0.8961
#> 3 1.355 1.2262 2.198 1.1661 1.0095
#> 4 1.006 0.9421 1.166 1.7480 0.7210
#> 5 1.074 0.8961 1.010 0.7210 1.5890
#> [1] "##################################################"
#> [1] "CALL"
#> [1] "##################################################"
#> [1] "lavaan::lavaan(model=model,data=df,missing=\"ML\",model.type=\"cfa\"," "cmd=\"cfa\",int.ov.free=TRUE,int.lv.free=FALSE,auto.fix.first=TRUE,"
#> [3] "auto.fix.single=TRUE,auto.var=TRUE,auto.cov.lv.x=TRUE," "auto.cov.y=TRUE,auto.th=TRUE,auto.delta=TRUE,auto.efa=TRUE)"
#> NULL
#> $r_squared
#> r_squared
#> ITEM1 0.4960
#> ITEM2 0.5121
#> ITEM3 0.6642
#> ITEM4 0.4778
#> ITEM5 0.4737
#>
#> $fit_indices
#> fit
#> npar 15.000000
#> fmin 0.003370
#> chisq 0.674046
#> df 5.000000
#> pvalue 0.984363
#> baseline.chisq 174.478659
#> baseline.df 10.000000
#> baseline.pvalue 0.000000
#> cfi 1.000000
#> tli 1.052602
#> cfi.robust 1.000000
#> tli.robust 1.055065
#> nnfi 1.052602
#> rfi 0.992274
#> nfi 0.996137
#> pnfi 0.498068
#> ifi 1.025525
#> rni 1.026301
#> nnfi.robust 1.055065
#> rni.robust 1.027533
#> logl -749.131822
#> unrestricted.logl -748.794799
#> aic 1528.263645
#> bic 1567.341197
#> ntotal 100.000000
#> bic2 1519.967429
#> rmsea 0.000000
#> rmsea.ci.lower 0.000000
#> rmsea.ci.upper 0.000000
#> rmsea.ci.level 0.900000
#> rmsea.pvalue 0.991126
#> rmsea.close.h0 0.050000
#> rmsea.notclose.pvalue 0.003662
#> rmsea.notclose.h0 0.080000
#> rmsea.robust 0.000000
#> rmsea.ci.lower.robust 0.000000
#> rmsea.ci.upper.robust 0.000000
#> rmsea.pvalue.robust 0.989151
#> rmsea.notclose.pvalue.robust 0.004981
#> rmr 0.019733
#> rmr_nomean 0.022770
#> srmr 0.010002
#> srmr_bentler 0.010002
#> srmr_bentler_nomean 0.011538
#> crmr 0.011490
#> crmr_nomean 0.014058
#> srmr_mplus 0.010000
#> srmr_mplus_nomean 0.011535
#> gfi 1.000000
#> gfi.ci.lower 1.000000
#> gfi.ci.upper 1.000000
#> gfi.ci.level 0.900000
#> gfi.robust 1.000000
#> gfi.ci.lower.robust 1.000000
#> gfi.ci.upper.robust 1.000000
#> cn_05 1643.395407
#> cn_01 2239.167181
#> gfi_lisrel 0.990266
#> agfi_lisrel 0.961064
#> pgfi 0.247566
#> mfi 1.021865
#> ecvi 0.306740
#>
#> $parameters
#> lhs op rhs exo est se z pvalue ci.lower ci.upper std.lv std.all
#> 1 LATENT =~ ITEM1 0 1.00000 0.0000 NA NA 1.0000 1.00000 1.11643 0.70424
#> 2 LATENT =~ ITEM2 0 0.89419 0.1451 6.1647 0.00000000070625 0.6099 1.17848 0.99829 0.71562
#> 3 LATENT =~ ITEM3 0 1.07504 0.1584 6.7855 0.00000000001157 0.7645 1.38555 1.20020 0.81498
#> 4 LATENT =~ ITEM4 0 0.81956 0.1395 5.8746 0.00000000423789 0.5461 1.09299 0.91498 0.69123
#> 5 LATENT =~ ITEM5 0 0.78140 0.1322 5.9106 0.00000000340802 0.5223 1.04051 0.87237 0.68825
#> 6 ITEM1 ~~ ITEM1 0 1.26674 0.2257 5.6124 0.00000001995429 0.8244 1.70911 1.26674 0.50405
#> 7 ITEM2 ~~ ITEM2 0 0.94947 0.1710 5.5531 0.00000002806169 0.6144 1.28458 0.94947 0.48789
#> 8 ITEM3 ~~ ITEM3 0 0.72828 0.1674 4.3510 0.00001355217445 0.4002 1.05634 0.72828 0.33581
#> 9 ITEM4 ~~ ITEM4 0 0.91499 0.1599 5.7229 0.00000001047405 0.6016 1.22836 0.91499 0.52220
#> 10 ITEM5 ~~ ITEM5 0 0.84560 0.1470 5.7529 0.00000000877034 0.5575 1.13368 0.84560 0.52632
#> 11 LATENT ~~ LATENT 0 1.24641 0.3379 3.6884 0.00022571087869 0.5841 1.90874 1.00000 1.00000
#> 12 ITEM1 ~1 0 -0.05338 0.1610 -0.3316 0.74021280963860 -0.3689 0.26217 -0.05338 -0.03367
#> 13 ITEM2 ~1 0 -0.20653 0.1417 -1.4580 0.14484703309578 -0.4842 0.07111 -0.20653 -0.14805
#> 14 ITEM3 ~1 0 -0.13891 0.1492 -0.9313 0.35170464156875 -0.4312 0.15343 -0.13891 -0.09432
#> 15 ITEM4 ~1 0 -0.08822 0.1345 -0.6561 0.51177311709724 -0.3518 0.17533 -0.08822 -0.06665
#> 16 ITEM5 ~1 0 -0.26501 0.1288 -2.0580 0.03958868413543 -0.5174 -0.01263 -0.26501 -0.20908
#> 17 LATENT ~1 0 0.00000 0.0000 NA NA 0.0000 0.00000 0.00000 0.00000
#> 18 ITEM1 r2 ITEM1 0 0.49595 NA NA NA NA NA NA NA
#> 19 ITEM2 r2 ITEM2 0 0.51211 NA NA NA NA NA NA NA
#> 20 ITEM3 r2 ITEM3 0 0.66419 NA NA NA NA NA NA NA
#> 21 ITEM4 r2 ITEM4 0 0.47780 NA NA NA NA NA NA NA
#> 22 ITEM5 r2 ITEM5 0 0.47368 NA NA NA NA NA NA NA
#>
#> $modification_indices
#> lhs op rhs mi epc sepc.all delta ncp power decision
#> 21 ITEM1 ~~ ITEM5 0.546839559868500080 0.105427920679 0.101866223045 0.1 0.4920 0.10799 (i)
#> 25 ITEM3 ~~ ITEM4 0.275767621240508021 0.073874994761 0.090498129420 0.1 0.5053 0.10959 (i)
#> 20 ITEM1 ~~ ITEM4 0.182608093538490890 -0.063586230775 -0.059062288848 0.1 0.4516 0.10313 (i)
#> 26 ITEM3 ~~ ITEM5 0.144146944786839315 -0.051078368338 -0.065088839207 0.1 0.5525 0.11530 (i)
#> 27 ITEM4 ~~ ITEM5 0.055751883265722953 -0.028087992141 -0.031932286682 0.1 0.7067 0.13405 (i)
#> 19 ITEM1 ~~ ITEM3 0.045199737013381272 -0.036087498532 -0.037571986417 0.1 0.3471 0.09061 (i)
#> 24 ITEM2 ~~ ITEM5 0.005416283716054107 -0.009202625795 -0.010270451024 0.1 0.6396 0.12587 (i)
#> 22 ITEM2 ~~ ITEM3 0.004474560269000743 0.010044330851 0.012079016583 0.1 0.4435 0.10215 (i)
#> 18 ITEM1 ~~ ITEM2 0.003803638239458201 -0.009638680153 -0.008788872998 0.1 0.4094 0.09806 (i)
#> 23 ITEM2 ~~ ITEM4 0.003578688330884250 0.007808557914 0.008377630806 0.1 0.5869 0.11947 (i)
#> 6 ITEM1 ~~ ITEM1 0.000000000006250995 -0.000000541352 -0.504045141476 0.1 0.2133 0.07477 (i)
#> 9 ITEM4 ~~ ITEM4 0.000000000000540229 0.000000113514 0.522204342330 0.1 0.4193 0.09924 (i)
#> 7 ITEM2 ~~ ITEM2 0.000000000000472315 0.000000112738 0.487893130267 0.1 0.3716 0.09354 (i)
#> 8 ITEM3 ~~ ITEM3 0.000000000000238537 -0.000000073629 -0.335805001662 0.1 0.4400 0.10173 (i)
#> 11 LATENT ~~ LATENT 0.000000000000178507 -0.000000088079 -1.000000000000 0.1 0.2301 0.07675 (i)
#> 2 LATENT =~ ITEM2 0.000000000000105779 0.000000033940 0.000000027162 0.1 0.9183 0.16001 (i)
#> 5 LATENT =~ ITEM5 0.000000000000088833 0.000000029060 0.000000025596 0.1 1.0519 0.17648 (i)
#> 12 ITEM1 ~1 0.000000000000036875 0.000000024070 0.000000015183 0.1 0.6365 0.12549 (i)
#> 4 LATENT =~ ITEM4 0.000000000000032181 0.000000018213 0.000000015361 0.1 0.9701 0.16639 (i)
#> 14 ITEM3 ~1 0.000000000000015834 0.000000013162 0.000000008938 0.1 0.9139 0.15947 (i)
#> 10 ITEM5 ~~ ITEM5 0.000000000000006525 -0.000000011499 -0.526317783477 0.1 0.4935 0.10817 (i)
#> 13 ITEM2 ~1 0.000000000000002848 0.000000005822 0.000000004173 0.1 0.8401 0.15040 (i)
#> 16 ITEM5 ~1 0.000000000000002491 0.000000005073 0.000000004002 0.1 0.9682 0.16615 (i)
#> 3 LATENT =~ ITEM3 0.000000000000002179 0.000000004575 0.000000003468 0.1 1.0411 0.17515 (i)
#> 15 ITEM4 ~1 0.000000000000002165 0.000000004925 0.000000003721 0.1 0.8924 0.15682 (i)
#>
#> $sample_covariance
#> X1 X2 X3 X4 X5
#> 1 2.526 1.1726 1.355 1.0057 1.0740
#> 2 1.173 1.9700 1.226 0.9421 0.8961
#> 3 1.355 1.2262 2.198 1.1661 1.0095
#> 4 1.006 0.9421 1.166 1.7480 0.7210
#> 5 1.074 0.8961 1.010 0.7210 1.5890
#>
#> $unstandardized_estimates
#> $lambda
#> LATENT
#> ITEM1 1.000
#> ITEM2 0.894
#> ITEM3 1.075
#> ITEM4 0.820
#> ITEM5 0.781
#>
#> $theta
#> ITEM1 ITEM2 ITEM3 ITEM4 ITEM5
#> ITEM1 1.267
#> ITEM2 0.000 0.949
#> ITEM3 0.000 0.000 0.728
#> ITEM4 0.000 0.000 0.000 0.915
#> ITEM5 0.000 0.000 0.000 0.000 0.846
#>
#> $psi
#> LATENT
#> LATENT 1.246
#>
#> $nu
#> intrcp
#> ITEM1 -0.053
#> ITEM2 -0.207
#> ITEM3 -0.139
#> ITEM4 -0.088
#> ITEM5 -0.265
#>
#> $alpha
#> intrcp
#> LATENT 0
#>
#>
#> $standardized_estimates
#> $lambda
#> LATENT
#> ITEM1 0.704
#> ITEM2 0.716
#> ITEM3 0.815
#> ITEM4 0.691
#> ITEM5 0.688
#>
#> $theta
#> ITEM1 ITEM2 ITEM3 ITEM4 ITEM5
#> ITEM1 0.504
#> ITEM2 0.000 0.488
#> ITEM3 0.000 0.000 0.336
#> ITEM4 0.000 0.000 0.000 0.522
#> ITEM5 0.000 0.000 0.000 0.000 0.526
#>
#> $psi
#> LATENT
#> LATENT 1
#>
#> $nu
#> intrcp
#> ITEM1 -0.034
#> ITEM2 -0.148
#> ITEM3 -0.094
#> ITEM4 -0.067
#> ITEM5 -0.209
#>
#> $alpha
#> intrcp
#> LATENT 0
#>
#>
#> $group
#> data frame with 0 columns and 0 rows
#>
#> $predict
#> X1 X2 X3 X4 X5 LATENT
#> 1 0.639786 NA NA -0.56123 -0.452156 -0.0162082
#> 2 -2.462159 -2.24205 -1.872255 -1.75436 -0.314500 -1.4452155
#> 3 -3.173193 -0.30594 -0.170723 -2.27201 -0.475878 -0.8680697
#> 4 2.391312 0.73163 -0.124045 1.33760 1.527821 1.0533706
#> 5 2.022265 1.41504 0.730857 1.39196 0.987034 1.2657522
#> 6 1.383443 1.13576 1.838407 1.81671 -0.060534 1.3168717
#> 7 -0.676032 1.25276 -0.678001 0.83943 1.200650 0.4148860
#> 8 1.109309 -1.60560 1.649983 0.22981 -0.582407 0.4076129
#> 9 -3.006267 -3.48008 -3.968901 -2.26092 -2.684625 -2.7843513
#> 10 1.241994 0.40066 NA -0.73485 0.759983 0.5044819
#> 11 -0.671821 -0.03584 0.968296 0.69037 1.602008 0.6809625
#> 12 0.009977 -1.27707 NA 1.27346 -0.855387 -0.0730292
#> 13 -1.440489 -0.72304 -0.390055 0.01643 -0.756342 -0.4222243
#> 14 -1.048633 NA -2.565442 -1.15141 -0.633791 -1.2213413
#> 15 -1.052949 1.25520 -1.977844 NA -0.813196 -0.5552705
#> 16 -2.705331 -2.95574 -0.624360 -0.90667 -1.773437 -1.3741800
#> 17 NA 0.04042 0.158792 -0.48458 0.268199 0.1727432
#> 18 -1.122548 0.03449 0.636602 -0.19419 NA 0.0910219
#> 19 1.724857 1.85038 1.016928 -0.82100 0.901207 0.9984535
#> 20 -0.823031 0.87220 -0.743756 -0.30193 -2.183369 -0.4470834
#> 21 2.247335 0.15024 1.529624 0.31685 0.619615 1.0581722
#> 22 -0.865883 -0.19776 -0.554558 -0.95455 -2.524469 -0.7505321
#> 23 NA -1.24310 -2.309152 -2.34084 -0.748606 -1.4174670
#> 24 1.286175 0.20415 1.333835 0.06162 0.833330 0.8704523
#> 25 -4.298038 -3.05750 -4.087274 -3.85652 0.133625 -2.7152280
#> 26 2.495902 -0.75263 2.528312 1.12448 -0.704335 1.1166151
#> 27 -0.823530 -0.59527 -2.098346 1.01561 0.040350 -0.4739180
#> 28 2.316649 -1.01674 -0.395587 -0.25432 0.382797 0.2152466
#> 29 1.626247 -2.54697 -0.550370 -0.17640 0.143733 -0.2167060
#> 30 -1.351659 NA -1.610394 0.82331 -1.100452 -0.6801976
#> 31 0.633766 0.61780 0.596913 -2.15710 0.318937 0.1992874
#> 32 -1.384579 -1.21795 -3.028885 -0.95312 -3.051564 -1.7563003
#> 33 0.007360 -0.32950 0.673445 -0.21368 -1.117877 0.0421390
#> 34 -2.826463 -0.46275 -1.690815 -1.18182 -2.640033 -1.4416026
#> 35 0.294657 -1.89621 -0.745613 1.04713 -0.005622 -0.1744611
#> 36 NA -0.26031 0.788891 0.65495 1.237793 0.7196342
#> 37 1.451930 -0.70076 -1.035591 -0.58223 -0.838214 -0.2871902
#> 38 -0.480311 -0.05407 0.171414 0.42461 0.052321 0.1857271
#> 39 0.090071 -0.66147 -1.579065 -0.05741 -0.205198 -0.4305728
#> 40 -1.669765 -1.49730 -1.257693 -1.03100 -2.229167 -1.2420526
#> 41 1.667761 -0.77184 0.656335 -0.16149 -0.603245 0.2961564
#> 42 -1.134263 -2.84989 -0.405335 -1.59245 -1.892230 -1.2026916
#> 43 1.062521 1.12370 -0.135651 0.04811 0.826208 0.5968680
#> 44 -0.999419 0.27077 -1.761869 0.07868 -1.134894 -0.6111817
#> 45 -0.156330 0.24365 -0.387066 0.61340 -1.305877 -0.0651862
#> 46 1.236885 0.74165 1.279900 -0.55135 0.616662 0.8044333
#> 47 0.604340 1.65448 0.448725 -0.40711 -0.060499 0.5555439
#> 48 1.354228 0.98154 -0.087781 -0.18221 -1.316586 0.2281679
#> 49 -1.964453 1.23789 -0.504673 -0.29547 -0.722946 -0.2368213
#> 50 1.323308 -0.42226 -0.201303 -1.07283 -0.152976 0.0023978
#> 51 -2.640016 -1.07243 -1.809780 -0.52287 0.577211 -0.9010428
#> 52 -0.741620 -1.77211 0.210706 1.15967 NA -0.0807453
#> 53 -1.453124 -2.29694 -1.306631 -3.21899 -1.807075 -1.6481260
#> 54 0.497749 -0.66202 -3.708221 -2.95105 NA -1.6460956
#> 55 0.808181 1.45290 0.851715 0.63938 0.451935 0.9164791
#> 56 1.132951 -0.44072 -0.157261 0.66816 0.604495 0.3961831
#> 57 -0.560108 -1.47832 0.000185 0.74542 -0.267699 -0.1183604
#> 58 -0.386646 -2.97814 -2.005607 0.19209 -1.914683 -1.2602329
#> 59 3.079060 0.42778 1.395911 1.83170 1.150547 1.5270627
#> 60 -0.129479 -1.52672 -1.488135 -2.20964 -2.527302 -1.3302641
#> 61 0.634189 2.20799 2.173958 1.65723 -1.036166 1.2929959
#> 62 1.185995 0.98461 2.321097 0.83858 1.171766 1.4404692
#> 63 1.701540 0.54735 NA 0.73202 0.418642 0.8899227
#> 64 NA -1.75139 0.118915 -1.17354 -1.054536 -0.5922253
#> 65 -1.219101 -3.37202 -1.765710 NA -1.286063 -1.5278554
#> 66 -1.282848 -0.55215 -0.303290 1.33225 -1.488990 -0.2551562
#> 67 -0.200893 -0.01939 1.193102 0.18210 2.383388 0.8609720
#> 68 1.069363 -1.14897 -0.602401 -3.05781 -0.841137 -0.7080046
#> 69 0.723955 1.10954 0.552389 -0.05279 -0.474423 0.4951276
#> 70 -1.769029 -0.39022 0.482808 -1.73143 0.156053 -0.3090007
#> 71 -0.607125 -0.83899 1.153078 -0.89711 -0.733107 -0.0516193
#> 72 2.082636 1.83798 NA 0.41960 0.407821 1.2052201
#> 73 -2.174829 -0.25616 -0.479623 -0.36643 -1.010068 -0.5773503
#> 74 1.969984 2.47497 1.156767 1.73831 3.616271 2.0555203
#> 75 2.392735 0.45617 0.296841 NA 1.624826 1.0425686
#> 76 -1.314367 -0.23376 -0.455483 NA NA -0.3701817
#> 77 0.797466 1.53080 0.703988 1.07348 1.328744 1.1074453
#> 78 -0.226802 NA -1.254460 -0.09453 -0.301778 -0.3933819
#> 79 -4.610416 -1.78377 -2.871683 -1.27790 -3.755634 -2.4480990
#> 80 2.451652 2.39100 -0.420545 1.17354 -1.116675 0.7944741
#> 81 -1.129669 -0.26796 1.301954 1.51736 -1.008650 0.3597530
#> 82 -0.115980 -0.11174 -0.474545 0.30391 1.002906 0.1948708
#> 83 0.160418 1.27257 0.741898 0.02651 0.418738 0.6566753
#> 84 -0.883454 2.13771 2.543341 NA 1.016580 1.4118395
#> 85 -1.039326 -0.11530 0.739306 -2.19353 -0.629758 -0.2955752
#> 86 -0.856566 -1.99731 -1.100760 -0.04275 0.597388 -0.5299975
#> 87 -1.078149 -0.62091 -0.032027 0.98580 -0.181584 -0.0004321
#> 88 1.663212 -0.29661 1.141832 1.60975 0.677057 1.0137568
#> 89 -0.282234 NA 1.521132 -0.52321 -0.202426 0.4181409
#> 90 -2.209001 -1.59546 -0.936984 0.97103 -1.271507 -0.7612236
#> 91 0.607963 1.45034 0.430476 2.03382 -0.275280 0.8789990
#> 92 -0.848125 -0.04688 -1.395504 -1.63656 -1.658392 -0.9140910
#> 93 0.933619 -0.07215 -1.067518 -0.37519 -0.113384 -0.1062550
#> 94 NA -1.26543 -2.310348 -0.59963 -0.468427 -1.0343780
#> 95 0.915919 -0.46984 -0.235870 -1.44221 -0.706289 -0.2275850
#> 96 0.802705 1.55491 0.522001 1.48089 -0.914367 0.7514624
#> 97 1.811700 1.08863 1.116562 2.46323 2.051236 1.6379804
#> 98 2.349805 2.26437 2.852502 2.31184 NA 2.2691915
#> 99 0.586106 0.80988 3.291084 2.35975 1.531432 1.8948454
#> 100 0.395401 2.45207 2.009135 1.19827 1.964904 1.6874133
#>
#> $call
#> call
#> 1 lavaan::lavaan(model=model,data=df,missing="ML",model.type="cfa",
#> 2 cmd="cfa",int.ov.free=TRUE,int.lv.free=FALSE,auto.fix.first=TRUE,
#> 3 auto.fix.single=TRUE,auto.var=TRUE,auto.cov.lv.x=TRUE,
#> 4 auto.cov.y=TRUE,auto.th=TRUE,auto.delta=TRUE,auto.efa=TRUE)
#>
report_cfa(fit,file="cfa")
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.labels' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.class' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'list.by.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'drop.list.single.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.labels' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.class' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'list.by.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'drop.list.single.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.labels' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.class' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'list.by.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'drop.list.single.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.labels' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'add.class' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'list.by.group' for 'inspect'
#> Warning: lavaan->inspect.lavaan():
#> Unknown argument 'drop.list.single.group' for 'inspect'
#> Skipping circle_parameters_wih_equality_constraints: replacement has 0 rows, data has 5
#> Skipping tree_parameters_wih_equality_constraints: replacement has 0 rows, data has 5
#> Skipping spring_parameters_wih_equality_constraints: replacement has 0 rows, data has 5
#> [1] "##################################################"
#> [1] "SUMMARY"
#> [1] "##################################################"
#> lavaan 0.7-3 ended normally after 26 iterations
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 15
#>
#> Number of observations 100
#> Number of missing patterns 8
#>
#> Model Test User Model:
#>
#> Test statistic 0.674
#> Degrees of freedom 5
#> P-value (Chi-square) 0.984
#>
#> Browne's residual (NT model-based) test
#> Test statistic 1.993
#> Degrees of freedom 5
#> P-value (Chi-square) 0.850
#>
#> Model Test Baseline Model:
#>
#> Test statistic 174.479
#> Degrees of freedom 10
#> P-value 0.000
#>
#> User Model versus Baseline Model:
#>
#> Comparative Fit Index (CFI) 1.000
#> Tucker-Lewis Index (TLI) 1.053
#>
#> Robust Comparative Fit Index (CFI) 1.000
#> Robust Tucker-Lewis Index (TLI) 1.055
#>
#> Loglikelihood and Information Criteria:
#>
#> Loglikelihood user model (H0) -749.132
#> Loglikelihood unrestricted model (H1) -748.795
#>
#> Akaike (AIC) 1528.264
#> Bayesian (BIC) 1567.341
#> Sample-size adjusted Bayesian (SABIC) 1519.967
#>
#> Root Mean Square Error of Approximation:
#>
#> RMSEA 0.000
#> 90 Percent confidence interval - lower 0.000
#> 90 Percent confidence interval - upper 0.000
#> P-value H_0: RMSEA <= 0.050 0.991
#> P-value H_0: RMSEA >= 0.080 0.004
#>
#> Robust RMSEA 0.000
#> 90 Percent confidence interval - lower 0.000
#> 90 Percent confidence interval - upper 0.000
#> P-value H_0: Robust RMSEA <= 0.050 0.989
#> P-value H_0: Robust RMSEA >= 0.080 0.005
#>
#> Standardized Root Mean Square Residual:
#>
#> SRMR 0.010
#>
#> Goodness of Fit Index:
#>
#> Goodness of Fit Index (GFI) 1.000
#> 90 Percent confidence interval - lower 1.000
#> 90 Percent confidence interval - upper 1.000
#>
#> Robust GFI 1.000
#> 90 Percent confidence interval - lower 1.000
#> 90 Percent confidence interval - upper 1.000
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Observed
#> Observed information based on Hessian
#>
#> Latent Variables:
#> Estimate Std.Err z-value P(>|z|) Std.lv Std.all
#> LATENT =~
#> ITEM1 1.000 1.116 0.704
#> ITEM2 0.894 0.145 6.165 0.000 0.998 0.716
#> ITEM3 1.075 0.158 6.786 0.000 1.200 0.815
#> ITEM4 0.820 0.140 5.875 0.000 0.915 0.691
#> ITEM5 0.781 0.132 5.911 0.000 0.872 0.688
#>
#> Intercepts:
#> Estimate Std.Err z-value P(>|z|) Std.lv Std.all
#> .ITEM1 -0.053 0.161 -0.332 0.740 -0.053 -0.034
#> .ITEM2 -0.207 0.142 -1.458 0.145 -0.207 -0.148
#> .ITEM3 -0.139 0.149 -0.931 0.352 -0.139 -0.094
#> .ITEM4 -0.088 0.134 -0.656 0.512 -0.088 -0.067
#> .ITEM5 -0.265 0.129 -2.058 0.040 -0.265 -0.209
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|) Std.lv Std.all
#> .ITEM1 1.267 0.226 5.612 0.000 1.267 0.504
#> .ITEM2 0.949 0.171 5.553 0.000 0.949 0.488
#> .ITEM3 0.728 0.167 4.351 0.000 0.728 0.336
#> .ITEM4 0.915 0.160 5.723 0.000 0.915 0.522
#> .ITEM5 0.846 0.147 5.753 0.000 0.846 0.526
#> LATENT 1.246 0.338 3.688 0.000 1.000 1.000
#>
#> R-Square:
#> Estimate
#> ITEM1 0.496
#> ITEM2 0.512
#> ITEM3 0.664
#> ITEM4 0.478
#> ITEM5 0.474
#>
#> [1] "##################################################"
#> [1] "R_SQUARED"
#> [1] "##################################################"
#> r_squared
#> ITEM1 0.4960
#> ITEM2 0.5121
#> ITEM3 0.6642
#> ITEM4 0.4778
#> ITEM5 0.4737
#> [1] "##################################################"
#> [1] "FIT INDICES"
#> [1] "##################################################"
#> fit
#> npar 15.000000
#> fmin 0.003370
#> chisq 0.674046
#> df 5.000000
#> pvalue 0.984363
#> baseline.chisq 174.478659
#> baseline.df 10.000000
#> baseline.pvalue 0.000000
#> cfi 1.000000
#> tli 1.052602
#> cfi.robust 1.000000
#> tli.robust 1.055065
#> nnfi 1.052602
#> rfi 0.992274
#> nfi 0.996137
#> pnfi 0.498068
#> ifi 1.025525
#> rni 1.026301
#> nnfi.robust 1.055065
#> rni.robust 1.027533
#> logl -749.131822
#> unrestricted.logl -748.794799
#> aic 1528.263645
#> bic 1567.341197
#> ntotal 100.000000
#> bic2 1519.967429
#> rmsea 0.000000
#> rmsea.ci.lower 0.000000
#> rmsea.ci.upper 0.000000
#> rmsea.ci.level 0.900000
#> rmsea.pvalue 0.991126
#> rmsea.close.h0 0.050000
#> rmsea.notclose.pvalue 0.003662
#> rmsea.notclose.h0 0.080000
#> rmsea.robust 0.000000
#> rmsea.ci.lower.robust 0.000000
#> rmsea.ci.upper.robust 0.000000
#> rmsea.pvalue.robust 0.989151
#> rmsea.notclose.pvalue.robust 0.004981
#> rmr 0.019733
#> rmr_nomean 0.022770
#> srmr 0.010002
#> srmr_bentler 0.010002
#> srmr_bentler_nomean 0.011538
#> crmr 0.011490
#> crmr_nomean 0.014058
#> srmr_mplus 0.010000
#> srmr_mplus_nomean 0.011535
#> gfi 1.000000
#> gfi.ci.lower 1.000000
#> gfi.ci.upper 1.000000
#> gfi.ci.level 0.900000
#> gfi.robust 1.000000
#> gfi.ci.lower.robust 1.000000
#> gfi.ci.upper.robust 1.000000
#> cn_05 1643.395407
#> cn_01 2239.167181
#> gfi_lisrel 0.990266
#> agfi_lisrel 0.961064
#> pgfi 0.247566
#> mfi 1.021865
#> ecvi 0.306740
#> [1] "##################################################"
#> [1] "PARAMETERS"
#> [1] "##################################################"
#> lhs op rhs exo est se z pvalue ci.lower ci.upper std.lv std.all
#> 1 LATENT =~ ITEM1 0 1.00000 0.0000 NA NA 1.0000 1.00000 1.11643 0.70424
#> 2 LATENT =~ ITEM2 0 0.89419 0.1451 6.1647 0.00000000070625 0.6099 1.17848 0.99829 0.71562
#> 3 LATENT =~ ITEM3 0 1.07504 0.1584 6.7855 0.00000000001157 0.7645 1.38555 1.20020 0.81498
#> 4 LATENT =~ ITEM4 0 0.81956 0.1395 5.8746 0.00000000423789 0.5461 1.09299 0.91498 0.69123
#> 5 LATENT =~ ITEM5 0 0.78140 0.1322 5.9106 0.00000000340802 0.5223 1.04051 0.87237 0.68825
#> 6 ITEM1 ~~ ITEM1 0 1.26674 0.2257 5.6124 0.00000001995429 0.8244 1.70911 1.26674 0.50405
#> 7 ITEM2 ~~ ITEM2 0 0.94947 0.1710 5.5531 0.00000002806169 0.6144 1.28458 0.94947 0.48789
#> 8 ITEM3 ~~ ITEM3 0 0.72828 0.1674 4.3510 0.00001355217445 0.4002 1.05634 0.72828 0.33581
#> 9 ITEM4 ~~ ITEM4 0 0.91499 0.1599 5.7229 0.00000001047405 0.6016 1.22836 0.91499 0.52220
#> 10 ITEM5 ~~ ITEM5 0 0.84560 0.1470 5.7529 0.00000000877034 0.5575 1.13368 0.84560 0.52632
#> 11 LATENT ~~ LATENT 0 1.24641 0.3379 3.6884 0.00022571087869 0.5841 1.90874 1.00000 1.00000
#> 12 ITEM1 ~1 0 -0.05338 0.1610 -0.3316 0.74021280963860 -0.3689 0.26217 -0.05338 -0.03367
#> 13 ITEM2 ~1 0 -0.20653 0.1417 -1.4580 0.14484703309578 -0.4842 0.07111 -0.20653 -0.14805
#> 14 ITEM3 ~1 0 -0.13891 0.1492 -0.9313 0.35170464156875 -0.4312 0.15343 -0.13891 -0.09432
#> 15 ITEM4 ~1 0 -0.08822 0.1345 -0.6561 0.51177311709724 -0.3518 0.17533 -0.08822 -0.06665
#> 16 ITEM5 ~1 0 -0.26501 0.1288 -2.0580 0.03958868413543 -0.5174 -0.01263 -0.26501 -0.20908
#> 17 LATENT ~1 0 0.00000 0.0000 NA NA 0.0000 0.00000 0.00000 0.00000
#> 18 ITEM1 r2 ITEM1 0 0.49595 NA NA NA NA NA NA NA
#> 19 ITEM2 r2 ITEM2 0 0.51211 NA NA NA NA NA NA NA
#> 20 ITEM3 r2 ITEM3 0 0.66419 NA NA NA NA NA NA NA
#> 21 ITEM4 r2 ITEM4 0 0.47780 NA NA NA NA NA NA NA
#> 22 ITEM5 r2 ITEM5 0 0.47368 NA NA NA NA NA NA NA
#> [1] "##################################################"
#> [1] "UNSTANDARDIZED PARAMETERS"
#> [1] "##################################################"
#> $lambda
#> LATENT
#> ITEM1 1.000
#> ITEM2 0.894
#> ITEM3 1.075
#> ITEM4 0.820
#> ITEM5 0.781
#>
#> $theta
#> ITEM1 ITEM2 ITEM3 ITEM4 ITEM5
#> ITEM1 1.267
#> ITEM2 0.000 0.949
#> ITEM3 0.000 0.000 0.728
#> ITEM4 0.000 0.000 0.000 0.915
#> ITEM5 0.000 0.000 0.000 0.000 0.846
#>
#> $psi
#> LATENT
#> LATENT 1.246
#>
#> $nu
#> intrcp
#> ITEM1 -0.053
#> ITEM2 -0.207
#> ITEM3 -0.139
#> ITEM4 -0.088
#> ITEM5 -0.265
#>
#> $alpha
#> intrcp
#> LATENT 0
#>
#> [1] "##################################################"
#> [1] "STANDARDIZED PARAMETERS"
#> [1] "##################################################"
#> $lambda
#> LATENT
#> ITEM1 0.704
#> ITEM2 0.716
#> ITEM3 0.815
#> ITEM4 0.691
#> ITEM5 0.688
#>
#> $theta
#> ITEM1 ITEM2 ITEM3 ITEM4 ITEM5
#> ITEM1 0.504
#> ITEM2 0.000 0.488
#> ITEM3 0.000 0.000 0.336
#> ITEM4 0.000 0.000 0.000 0.522
#> ITEM5 0.000 0.000 0.000 0.000 0.526
#>
#> $psi
#> LATENT
#> LATENT 1
#>
#> $nu
#> intrcp
#> ITEM1 -0.034
#> ITEM2 -0.148
#> ITEM3 -0.094
#> ITEM4 -0.067
#> ITEM5 -0.209
#>
#> $alpha
#> intrcp
#> LATENT 0
#>
#> [1] "##################################################"
#> [1] "SAMPLE COVARIANCE"
#> [1] "##################################################"
#> X1 X2 X3 X4 X5
#> 1 2.526 1.1726 1.355 1.0057 1.0740
#> 2 1.173 1.9700 1.226 0.9421 0.8961
#> 3 1.355 1.2262 2.198 1.1661 1.0095
#> 4 1.006 0.9421 1.166 1.7480 0.7210
#> 5 1.074 0.8961 1.010 0.7210 1.5890
#> [1] "##################################################"
#> [1] "CALL"
#> [1] "##################################################"
#> [1] "lavaan::lavaan(model=model,data=df,missing=\"ML\",model.type=\"cfa\"," "cmd=\"cfa\",int.ov.free=TRUE,int.lv.free=FALSE,auto.fix.first=TRUE,"
#> [3] "auto.fix.single=TRUE,auto.var=TRUE,auto.cov.lv.x=TRUE," "auto.cov.y=TRUE,auto.th=TRUE,auto.delta=TRUE,auto.efa=TRUE)"
#> NULL
#> $r_squared
#> r_squared
#> ITEM1 0.4960
#> ITEM2 0.5121
#> ITEM3 0.6642
#> ITEM4 0.4778
#> ITEM5 0.4737
#>
#> $fit_indices
#> fit
#> npar 15.000000
#> fmin 0.003370
#> chisq 0.674046
#> df 5.000000
#> pvalue 0.984363
#> baseline.chisq 174.478659
#> baseline.df 10.000000
#> baseline.pvalue 0.000000
#> cfi 1.000000
#> tli 1.052602
#> cfi.robust 1.000000
#> tli.robust 1.055065
#> nnfi 1.052602
#> rfi 0.992274
#> nfi 0.996137
#> pnfi 0.498068
#> ifi 1.025525
#> rni 1.026301
#> nnfi.robust 1.055065
#> rni.robust 1.027533
#> logl -749.131822
#> unrestricted.logl -748.794799
#> aic 1528.263645
#> bic 1567.341197
#> ntotal 100.000000
#> bic2 1519.967429
#> rmsea 0.000000
#> rmsea.ci.lower 0.000000
#> rmsea.ci.upper 0.000000
#> rmsea.ci.level 0.900000
#> rmsea.pvalue 0.991126
#> rmsea.close.h0 0.050000
#> rmsea.notclose.pvalue 0.003662
#> rmsea.notclose.h0 0.080000
#> rmsea.robust 0.000000
#> rmsea.ci.lower.robust 0.000000
#> rmsea.ci.upper.robust 0.000000
#> rmsea.pvalue.robust 0.989151
#> rmsea.notclose.pvalue.robust 0.004981
#> rmr 0.019733
#> rmr_nomean 0.022770
#> srmr 0.010002
#> srmr_bentler 0.010002
#> srmr_bentler_nomean 0.011538
#> crmr 0.011490
#> crmr_nomean 0.014058
#> srmr_mplus 0.010000
#> srmr_mplus_nomean 0.011535
#> gfi 1.000000
#> gfi.ci.lower 1.000000
#> gfi.ci.upper 1.000000
#> gfi.ci.level 0.900000
#> gfi.robust 1.000000
#> gfi.ci.lower.robust 1.000000
#> gfi.ci.upper.robust 1.000000
#> cn_05 1643.395407
#> cn_01 2239.167181
#> gfi_lisrel 0.990266
#> agfi_lisrel 0.961064
#> pgfi 0.247566
#> mfi 1.021865
#> ecvi 0.306740
#>
#> $parameters
#> lhs op rhs exo est se z pvalue ci.lower ci.upper std.lv std.all
#> 1 LATENT =~ ITEM1 0 1.00000 0.0000 NA NA 1.0000 1.00000 1.11643 0.70424
#> 2 LATENT =~ ITEM2 0 0.89419 0.1451 6.1647 0.00000000070625 0.6099 1.17848 0.99829 0.71562
#> 3 LATENT =~ ITEM3 0 1.07504 0.1584 6.7855 0.00000000001157 0.7645 1.38555 1.20020 0.81498
#> 4 LATENT =~ ITEM4 0 0.81956 0.1395 5.8746 0.00000000423789 0.5461 1.09299 0.91498 0.69123
#> 5 LATENT =~ ITEM5 0 0.78140 0.1322 5.9106 0.00000000340802 0.5223 1.04051 0.87237 0.68825
#> 6 ITEM1 ~~ ITEM1 0 1.26674 0.2257 5.6124 0.00000001995429 0.8244 1.70911 1.26674 0.50405
#> 7 ITEM2 ~~ ITEM2 0 0.94947 0.1710 5.5531 0.00000002806169 0.6144 1.28458 0.94947 0.48789
#> 8 ITEM3 ~~ ITEM3 0 0.72828 0.1674 4.3510 0.00001355217445 0.4002 1.05634 0.72828 0.33581
#> 9 ITEM4 ~~ ITEM4 0 0.91499 0.1599 5.7229 0.00000001047405 0.6016 1.22836 0.91499 0.52220
#> 10 ITEM5 ~~ ITEM5 0 0.84560 0.1470 5.7529 0.00000000877034 0.5575 1.13368 0.84560 0.52632
#> 11 LATENT ~~ LATENT 0 1.24641 0.3379 3.6884 0.00022571087869 0.5841 1.90874 1.00000 1.00000
#> 12 ITEM1 ~1 0 -0.05338 0.1610 -0.3316 0.74021280963860 -0.3689 0.26217 -0.05338 -0.03367
#> 13 ITEM2 ~1 0 -0.20653 0.1417 -1.4580 0.14484703309578 -0.4842 0.07111 -0.20653 -0.14805
#> 14 ITEM3 ~1 0 -0.13891 0.1492 -0.9313 0.35170464156875 -0.4312 0.15343 -0.13891 -0.09432
#> 15 ITEM4 ~1 0 -0.08822 0.1345 -0.6561 0.51177311709724 -0.3518 0.17533 -0.08822 -0.06665
#> 16 ITEM5 ~1 0 -0.26501 0.1288 -2.0580 0.03958868413543 -0.5174 -0.01263 -0.26501 -0.20908
#> 17 LATENT ~1 0 0.00000 0.0000 NA NA 0.0000 0.00000 0.00000 0.00000
#> 18 ITEM1 r2 ITEM1 0 0.49595 NA NA NA NA NA NA NA
#> 19 ITEM2 r2 ITEM2 0 0.51211 NA NA NA NA NA NA NA
#> 20 ITEM3 r2 ITEM3 0 0.66419 NA NA NA NA NA NA NA
#> 21 ITEM4 r2 ITEM4 0 0.47780 NA NA NA NA NA NA NA
#> 22 ITEM5 r2 ITEM5 0 0.47368 NA NA NA NA NA NA NA
#>
#> $modification_indices
#> lhs op rhs mi epc sepc.all delta ncp power decision
#> 21 ITEM1 ~~ ITEM5 0.546839559868500080 0.105427920679 0.101866223045 0.1 0.4920 0.10799 (i)
#> 25 ITEM3 ~~ ITEM4 0.275767621240508021 0.073874994761 0.090498129420 0.1 0.5053 0.10959 (i)
#> 20 ITEM1 ~~ ITEM4 0.182608093538490890 -0.063586230775 -0.059062288848 0.1 0.4516 0.10313 (i)
#> 26 ITEM3 ~~ ITEM5 0.144146944786839315 -0.051078368338 -0.065088839207 0.1 0.5525 0.11530 (i)
#> 27 ITEM4 ~~ ITEM5 0.055751883265722953 -0.028087992141 -0.031932286682 0.1 0.7067 0.13405 (i)
#> 19 ITEM1 ~~ ITEM3 0.045199737013381272 -0.036087498532 -0.037571986417 0.1 0.3471 0.09061 (i)
#> 24 ITEM2 ~~ ITEM5 0.005416283716054107 -0.009202625795 -0.010270451024 0.1 0.6396 0.12587 (i)
#> 22 ITEM2 ~~ ITEM3 0.004474560269000743 0.010044330851 0.012079016583 0.1 0.4435 0.10215 (i)
#> 18 ITEM1 ~~ ITEM2 0.003803638239458201 -0.009638680153 -0.008788872998 0.1 0.4094 0.09806 (i)
#> 23 ITEM2 ~~ ITEM4 0.003578688330884250 0.007808557914 0.008377630806 0.1 0.5869 0.11947 (i)
#> 6 ITEM1 ~~ ITEM1 0.000000000006250995 -0.000000541352 -0.504045141476 0.1 0.2133 0.07477 (i)
#> 9 ITEM4 ~~ ITEM4 0.000000000000540229 0.000000113514 0.522204342330 0.1 0.4193 0.09924 (i)
#> 7 ITEM2 ~~ ITEM2 0.000000000000472315 0.000000112738 0.487893130267 0.1 0.3716 0.09354 (i)
#> 8 ITEM3 ~~ ITEM3 0.000000000000238537 -0.000000073629 -0.335805001662 0.1 0.4400 0.10173 (i)
#> 11 LATENT ~~ LATENT 0.000000000000178507 -0.000000088079 -1.000000000000 0.1 0.2301 0.07675 (i)
#> 2 LATENT =~ ITEM2 0.000000000000105779 0.000000033940 0.000000027162 0.1 0.9183 0.16001 (i)
#> 5 LATENT =~ ITEM5 0.000000000000088833 0.000000029060 0.000000025596 0.1 1.0519 0.17648 (i)
#> 12 ITEM1 ~1 0.000000000000036875 0.000000024070 0.000000015183 0.1 0.6365 0.12549 (i)
#> 4 LATENT =~ ITEM4 0.000000000000032181 0.000000018213 0.000000015361 0.1 0.9701 0.16639 (i)
#> 14 ITEM3 ~1 0.000000000000015834 0.000000013162 0.000000008938 0.1 0.9139 0.15947 (i)
#> 10 ITEM5 ~~ ITEM5 0.000000000000006525 -0.000000011499 -0.526317783477 0.1 0.4935 0.10817 (i)
#> 13 ITEM2 ~1 0.000000000000002848 0.000000005822 0.000000004173 0.1 0.8401 0.15040 (i)
#> 16 ITEM5 ~1 0.000000000000002491 0.000000005073 0.000000004002 0.1 0.9682 0.16615 (i)
#> 3 LATENT =~ ITEM3 0.000000000000002179 0.000000004575 0.000000003468 0.1 1.0411 0.17515 (i)
#> 15 ITEM4 ~1 0.000000000000002165 0.000000004925 0.000000003721 0.1 0.8924 0.15682 (i)
#>
#> $sample_covariance
#> X1 X2 X3 X4 X5
#> 1 2.526 1.1726 1.355 1.0057 1.0740
#> 2 1.173 1.9700 1.226 0.9421 0.8961
#> 3 1.355 1.2262 2.198 1.1661 1.0095
#> 4 1.006 0.9421 1.166 1.7480 0.7210
#> 5 1.074 0.8961 1.010 0.7210 1.5890
#>
#> $unstandardized_estimates
#> $lambda
#> LATENT
#> ITEM1 1.000
#> ITEM2 0.894
#> ITEM3 1.075
#> ITEM4 0.820
#> ITEM5 0.781
#>
#> $theta
#> ITEM1 ITEM2 ITEM3 ITEM4 ITEM5
#> ITEM1 1.267
#> ITEM2 0.000 0.949
#> ITEM3 0.000 0.000 0.728
#> ITEM4 0.000 0.000 0.000 0.915
#> ITEM5 0.000 0.000 0.000 0.000 0.846
#>
#> $psi
#> LATENT
#> LATENT 1.246
#>
#> $nu
#> intrcp
#> ITEM1 -0.053
#> ITEM2 -0.207
#> ITEM3 -0.139
#> ITEM4 -0.088
#> ITEM5 -0.265
#>
#> $alpha
#> intrcp
#> LATENT 0
#>
#>
#> $standardized_estimates
#> $lambda
#> LATENT
#> ITEM1 0.704
#> ITEM2 0.716
#> ITEM3 0.815
#> ITEM4 0.691
#> ITEM5 0.688
#>
#> $theta
#> ITEM1 ITEM2 ITEM3 ITEM4 ITEM5
#> ITEM1 0.504
#> ITEM2 0.000 0.488
#> ITEM3 0.000 0.000 0.336
#> ITEM4 0.000 0.000 0.000 0.522
#> ITEM5 0.000 0.000 0.000 0.000 0.526
#>
#> $psi
#> LATENT
#> LATENT 1
#>
#> $nu
#> intrcp
#> ITEM1 -0.034
#> ITEM2 -0.148
#> ITEM3 -0.094
#> ITEM4 -0.067
#> ITEM5 -0.209
#>
#> $alpha
#> intrcp
#> LATENT 0
#>
#>
#> $group
#> data frame with 0 columns and 0 rows
#>
#> $predict
#> X1 X2 X3 X4 X5 LATENT
#> 1 0.639786 NA NA -0.56123 -0.452156 -0.0162082
#> 2 -2.462159 -2.24205 -1.872255 -1.75436 -0.314500 -1.4452155
#> 3 -3.173193 -0.30594 -0.170723 -2.27201 -0.475878 -0.8680697
#> 4 2.391312 0.73163 -0.124045 1.33760 1.527821 1.0533706
#> 5 2.022265 1.41504 0.730857 1.39196 0.987034 1.2657522
#> 6 1.383443 1.13576 1.838407 1.81671 -0.060534 1.3168717
#> 7 -0.676032 1.25276 -0.678001 0.83943 1.200650 0.4148860
#> 8 1.109309 -1.60560 1.649983 0.22981 -0.582407 0.4076129
#> 9 -3.006267 -3.48008 -3.968901 -2.26092 -2.684625 -2.7843513
#> 10 1.241994 0.40066 NA -0.73485 0.759983 0.5044819
#> 11 -0.671821 -0.03584 0.968296 0.69037 1.602008 0.6809625
#> 12 0.009977 -1.27707 NA 1.27346 -0.855387 -0.0730292
#> 13 -1.440489 -0.72304 -0.390055 0.01643 -0.756342 -0.4222243
#> 14 -1.048633 NA -2.565442 -1.15141 -0.633791 -1.2213413
#> 15 -1.052949 1.25520 -1.977844 NA -0.813196 -0.5552705
#> 16 -2.705331 -2.95574 -0.624360 -0.90667 -1.773437 -1.3741800
#> 17 NA 0.04042 0.158792 -0.48458 0.268199 0.1727432
#> 18 -1.122548 0.03449 0.636602 -0.19419 NA 0.0910219
#> 19 1.724857 1.85038 1.016928 -0.82100 0.901207 0.9984535
#> 20 -0.823031 0.87220 -0.743756 -0.30193 -2.183369 -0.4470834
#> 21 2.247335 0.15024 1.529624 0.31685 0.619615 1.0581722
#> 22 -0.865883 -0.19776 -0.554558 -0.95455 -2.524469 -0.7505321
#> 23 NA -1.24310 -2.309152 -2.34084 -0.748606 -1.4174670
#> 24 1.286175 0.20415 1.333835 0.06162 0.833330 0.8704523
#> 25 -4.298038 -3.05750 -4.087274 -3.85652 0.133625 -2.7152280
#> 26 2.495902 -0.75263 2.528312 1.12448 -0.704335 1.1166151
#> 27 -0.823530 -0.59527 -2.098346 1.01561 0.040350 -0.4739180
#> 28 2.316649 -1.01674 -0.395587 -0.25432 0.382797 0.2152466
#> 29 1.626247 -2.54697 -0.550370 -0.17640 0.143733 -0.2167060
#> 30 -1.351659 NA -1.610394 0.82331 -1.100452 -0.6801976
#> 31 0.633766 0.61780 0.596913 -2.15710 0.318937 0.1992874
#> 32 -1.384579 -1.21795 -3.028885 -0.95312 -3.051564 -1.7563003
#> 33 0.007360 -0.32950 0.673445 -0.21368 -1.117877 0.0421390
#> 34 -2.826463 -0.46275 -1.690815 -1.18182 -2.640033 -1.4416026
#> 35 0.294657 -1.89621 -0.745613 1.04713 -0.005622 -0.1744611
#> 36 NA -0.26031 0.788891 0.65495 1.237793 0.7196342
#> 37 1.451930 -0.70076 -1.035591 -0.58223 -0.838214 -0.2871902
#> 38 -0.480311 -0.05407 0.171414 0.42461 0.052321 0.1857271
#> 39 0.090071 -0.66147 -1.579065 -0.05741 -0.205198 -0.4305728
#> 40 -1.669765 -1.49730 -1.257693 -1.03100 -2.229167 -1.2420526
#> 41 1.667761 -0.77184 0.656335 -0.16149 -0.603245 0.2961564
#> 42 -1.134263 -2.84989 -0.405335 -1.59245 -1.892230 -1.2026916
#> 43 1.062521 1.12370 -0.135651 0.04811 0.826208 0.5968680
#> 44 -0.999419 0.27077 -1.761869 0.07868 -1.134894 -0.6111817
#> 45 -0.156330 0.24365 -0.387066 0.61340 -1.305877 -0.0651862
#> 46 1.236885 0.74165 1.279900 -0.55135 0.616662 0.8044333
#> 47 0.604340 1.65448 0.448725 -0.40711 -0.060499 0.5555439
#> 48 1.354228 0.98154 -0.087781 -0.18221 -1.316586 0.2281679
#> 49 -1.964453 1.23789 -0.504673 -0.29547 -0.722946 -0.2368213
#> 50 1.323308 -0.42226 -0.201303 -1.07283 -0.152976 0.0023978
#> 51 -2.640016 -1.07243 -1.809780 -0.52287 0.577211 -0.9010428
#> 52 -0.741620 -1.77211 0.210706 1.15967 NA -0.0807453
#> 53 -1.453124 -2.29694 -1.306631 -3.21899 -1.807075 -1.6481260
#> 54 0.497749 -0.66202 -3.708221 -2.95105 NA -1.6460956
#> 55 0.808181 1.45290 0.851715 0.63938 0.451935 0.9164791
#> 56 1.132951 -0.44072 -0.157261 0.66816 0.604495 0.3961831
#> 57 -0.560108 -1.47832 0.000185 0.74542 -0.267699 -0.1183604
#> 58 -0.386646 -2.97814 -2.005607 0.19209 -1.914683 -1.2602329
#> 59 3.079060 0.42778 1.395911 1.83170 1.150547 1.5270627
#> 60 -0.129479 -1.52672 -1.488135 -2.20964 -2.527302 -1.3302641
#> 61 0.634189 2.20799 2.173958 1.65723 -1.036166 1.2929959
#> 62 1.185995 0.98461 2.321097 0.83858 1.171766 1.4404692
#> 63 1.701540 0.54735 NA 0.73202 0.418642 0.8899227
#> 64 NA -1.75139 0.118915 -1.17354 -1.054536 -0.5922253
#> 65 -1.219101 -3.37202 -1.765710 NA -1.286063 -1.5278554
#> 66 -1.282848 -0.55215 -0.303290 1.33225 -1.488990 -0.2551562
#> 67 -0.200893 -0.01939 1.193102 0.18210 2.383388 0.8609720
#> 68 1.069363 -1.14897 -0.602401 -3.05781 -0.841137 -0.7080046
#> 69 0.723955 1.10954 0.552389 -0.05279 -0.474423 0.4951276
#> 70 -1.769029 -0.39022 0.482808 -1.73143 0.156053 -0.3090007
#> 71 -0.607125 -0.83899 1.153078 -0.89711 -0.733107 -0.0516193
#> 72 2.082636 1.83798 NA 0.41960 0.407821 1.2052201
#> 73 -2.174829 -0.25616 -0.479623 -0.36643 -1.010068 -0.5773503
#> 74 1.969984 2.47497 1.156767 1.73831 3.616271 2.0555203
#> 75 2.392735 0.45617 0.296841 NA 1.624826 1.0425686
#> 76 -1.314367 -0.23376 -0.455483 NA NA -0.3701817
#> 77 0.797466 1.53080 0.703988 1.07348 1.328744 1.1074453
#> 78 -0.226802 NA -1.254460 -0.09453 -0.301778 -0.3933819
#> 79 -4.610416 -1.78377 -2.871683 -1.27790 -3.755634 -2.4480990
#> 80 2.451652 2.39100 -0.420545 1.17354 -1.116675 0.7944741
#> 81 -1.129669 -0.26796 1.301954 1.51736 -1.008650 0.3597530
#> 82 -0.115980 -0.11174 -0.474545 0.30391 1.002906 0.1948708
#> 83 0.160418 1.27257 0.741898 0.02651 0.418738 0.6566753
#> 84 -0.883454 2.13771 2.543341 NA 1.016580 1.4118395
#> 85 -1.039326 -0.11530 0.739306 -2.19353 -0.629758 -0.2955752
#> 86 -0.856566 -1.99731 -1.100760 -0.04275 0.597388 -0.5299975
#> 87 -1.078149 -0.62091 -0.032027 0.98580 -0.181584 -0.0004321
#> 88 1.663212 -0.29661 1.141832 1.60975 0.677057 1.0137568
#> 89 -0.282234 NA 1.521132 -0.52321 -0.202426 0.4181409
#> 90 -2.209001 -1.59546 -0.936984 0.97103 -1.271507 -0.7612236
#> 91 0.607963 1.45034 0.430476 2.03382 -0.275280 0.8789990
#> 92 -0.848125 -0.04688 -1.395504 -1.63656 -1.658392 -0.9140910
#> 93 0.933619 -0.07215 -1.067518 -0.37519 -0.113384 -0.1062550
#> 94 NA -1.26543 -2.310348 -0.59963 -0.468427 -1.0343780
#> 95 0.915919 -0.46984 -0.235870 -1.44221 -0.706289 -0.2275850
#> 96 0.802705 1.55491 0.522001 1.48089 -0.914367 0.7514624
#> 97 1.811700 1.08863 1.116562 2.46323 2.051236 1.6379804
#> 98 2.349805 2.26437 2.852502 2.31184 NA 2.2691915
#> 99 0.586106 0.80988 3.291084 2.35975 1.531432 1.8948454
#> 100 0.395401 2.45207 2.009135 1.19827 1.964904 1.6874133
#>
#> $call
#> call
#> 1 lavaan::lavaan(model=model,data=df,missing="ML",model.type="cfa",
#> 2 cmd="cfa",int.ov.free=TRUE,int.lv.free=FALSE,auto.fix.first=TRUE,
#> 3 auto.fix.single=TRUE,auto.var=TRUE,auto.cov.lv.x=TRUE,
#> 4 auto.cov.y=TRUE,auto.th=TRUE,auto.delta=TRUE,auto.efa=TRUE)
#>