search for: nnfi

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2013 Apr 28
0
hierarchical confirmatory factor analysis with sem package
...1 and F2 are nested within F3. Here is the code that I have, but it is giving me an error message "Warning message: In eval(expr, envir, enclos) : Negative parameter variances. Model may be underidentified." and a further error "Error in summary.objectiveML(cfa, fit.indices = c("NNFI", "CFI", "RMSEA")) : coefficient covariances cannot be computed". I have run CFA before with no issues. This is the first time I am running a nested model. Any help will be greatly appreciated. Regards, Mat cov.matrix<-cov(na.omit(df)) cfa.model<-specifyModel() F...
2009 Mar 09
2
path analysis (misspecification?)
...esults; Model Chisquare = 12.524 Df = 1 Pr(>Chisq) = 0.00040179 Chisquare (null model) = 812.69 Df = 3 Goodness-of-fit index = 0.98083 Adjusted goodness-of-fit index = 0.885 RMSEA index = 0.16545 90% CI: (0.09231, 0.25264) Bentler-Bonnett NFI = 0.98459 Tucker-Lewis NNFI = 0.9573 Bentler CFI = 0.98577 SRMR = 0.027022 BIC = 6.4789 Parameter Estimates Estimate Std Error z value Pr(>|z|) x1-y1 -0.67833 0.033967 -19.970 0 y1 <--- x1 x2-x1 3.88384 0.293743 13.222 0 x1 <--> x2 x2-x2 12.05082 0.831569 14.492 0 x2...
2007 Mar 07
1
No fit statistics for some models using sem
...all the usual statistics: Model Chisquare = 1303.7 Df = 1 Pr(>Chisq) = 0 Chisquare (null model) = 8526.8 Df = 6 Goodness-of-fit index = 0.95864 Adjusted goodness-of-fit index = 0.58639 RMSEA index = 0.30029 90% CI: (NA, NA) Bentler-Bonnett NFI = 0.84711 Tucker-Lewis NNFI = 0.082726 Bentler CFI = 0.84712 BIC = 1294.1 My understanding is the you should always put in the correlation between exogenous predictors, but when I do this I don't get fit statistics. Can anyone help me understand what is happening here? Thank you, Ista
2007 Jun 27
1
SEM model fit
...rning messages with the output. RESULTS: Model Chisquare = 1374 Df = 185 Pr(>Chisq) = 0 Chisquare (null model) = 12284 Df = 210 Goodness-of-fit index = 0.903 Adjusted goodness-of-fit index = 0.88 RMSEA index = 0.0711 90% CI: (NA, NA) Bentler-Bonnett NFI = 0.888 Tucker-Lewis NNFI = 0.888 Bentler CFI = 0.902 SRMR = 0.0682 BIC = 51.4 SYNTAX rm(sem.enf.rq) mdl.rq <- specify.model() enf -> law2, NA, 1 enf -> law3, lam2, 1 enf -> law4, lam3, 1 enf <->...
2006 Aug 16
1
Specifying Path Model in SEM for CFA
...converges: > summary(fit.sem) Model Chisquare = 2147 Df = 10 Pr(>Chisq) = 0 Chisquare (null model) = 2934 Df = 15 Goodness-of-fit index = 0.4822 Adjusted goodness-of-fit index = -0.087387 RMSEA index = 0.66107 90 % CI: (NA, NA) Bentler-Bonnett NFI = 0.26823 Tucker-Lewis NNFI = -0.098156 Bentler CFI = 0.26790 BIC = 2085.1 Normalized Residuals Min. 1st Qu. Median Mean 3rd Qu. Max. -5.990 -0.618 0.192 0.165 1.700 3.950 Parameter Estimates Estimate Std Error z value Pr(>|z|) l11 -0.245981 0.21863 -1.12510 0.26054748 X1 <--- F1 l21...
2007 Feb 20
0
Standardized residual variances in SEM
...t; summary(semModif.tmp, digits=2) Model Chisquare = 601 Df = 229 Pr(>Chisq) = 0 Chisquare (null model) = 2936 Df = 253 Goodness-of-fit index = 0.81 Adjusted goodness-of-fit index = 0.78 RMSEA index = 0.08 90% CI: (0.072, 0.088) Bentler-Bonnett NFI = 0.8 Tucker-Lewis NNFI = 0.85 Bentler CFI = 0.86 BIC = -667 Normalized Residuals Min. 1st Qu. Median Mean 3rd Qu. Max. -2.6300 -0.5640 -0.0728 -0.0067 0.5530 3.5500 Parameter Estimates Estimate Std Error z value Pr(>|z|) param1 0.78 0.073 10.7 0.0e+00 Q1 <--- G param2...
2006 Aug 22
1
Total (un)standardized effects in SEM?
Hi there, as a student sociology, I'm starting to learn about SEM. The course I follow is based on LISREL, but I want to use the SEM-package on R parallel to it. Using LISREL, I found it to be very usable to be able to see the total direct and total indirect effects (standardized and unstandardized) in the output. Can I create these effects using R? I know how to calculate them
2008 Dec 22
1
sem package fails when no of factors increase from 3 to 4
#### I checked through every 3 factor * 3 loading case. #### While, 4 factor * 3 loading failed. #### the data is 6 factor * 3 loading require(sem); cor18<-read.moments(); 1 .68 1 .60 .58 1 .01 .10 .07 1 .12 .04 .06 .29 1 .06 .06 .01 .35 .24 1 .09 .13 .10 .05 .03 .07 1 .04 .08 .16 .10 .12 .06 .25 1 .06 .09 .02 .02 .09 .16 .29 .36 1 .23 .26 .19 .05 .04 .04 .08 .09 .09 1 .11 .13 .12 .03 .05 .03
2008 Dec 29
0
Serial Correlation Test for Short Time Series
...or18, 500)) Model Chisquare = 80.675 Df = 48 Pr(>Chisq) = 0.0021920 Chisquare (null model) = 1106.4 Df = 66 Goodness-of-fit index = 0.9747 Adjusted goodness-of-fit index = 0.95888 RMSEA index = 0.036935 90% CI: (0.022163, 0.050657) Bentler-Bonnett NFI = 0.92708 Tucker-Lewis NNFI = 0.95682 Bentler CFI = 0.9686 SRMR = 0.032512 BIC = -217.63 Normalized Residuals Min. 1st Qu. Median Mean 3rd Qu. Max. -1.71000 -0.23300 -0.00337 0.08850 0.26700 2.13000 Parameter Estimates Estimate Std Error z value Pr(>|z|) TD11 0.30641 0.037053 8.2694 2....