[R] No fit statistics for some models using sem
Hi, New to both R and SEM, so this may be a very simple question. I am trying to run a very simple path analysis using the sem package. There are 2 exogenous (FARSCH, LOCUS10) and 2 endogenous (T_ATTENT, RMTEST) observed variables in the model. The idea is that T_ATTENT mediates the effect of FARSCH and LOCUS10 on RMTEST. The RAM specification I used is FARSCH - T_ATTENT, y1x1, NA LOCUS10 - T_ATTENT, y1x2, NA FARSCH - RMTEST10, y2x1, NA LOCUS10 - RMTEST10, y2x2, NA T_ATTENT - RMTEST10, y2y1, NA FARSCH - FARSCH, x1x1, NA LOCUS10 - LOCUS10, x2x2, NA T_ATTENT - T_ATTENT, y1y1, NA RMTEST10 - RMTEST10, y2y2, NA LOCUS10 - FARSCH, x2x1, NA This model runs, but using the summary function does not return the usual model fit statistics, only the following: Model Chisquare = 0 Df = 0 Pr(Chisq) = NA Chisquare (null model) = 8526.8 Df = 6 Goodness-of-fit index = 1 BIC = 0 If I omit the last line from the RAM specification(i.e., delete LOCUS10 - FARSCH, x2x1, NA), I DO get 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 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] No fit statistics for some models using sem
It's not the correlation as such that is the problem; it's because you only have 10 degrees of freedom available with four observed variables, and you are estimating 10 parameters, which is why you get a chi square of zero. When you remove any one free parameter (such as the correlation), the model becomes identified. On 07/03/07, Ista Zahn [EMAIL PROTECTED] wrote: Hi, New to both R and SEM, so this may be a very simple question. I am trying to run a very simple path analysis using the sem package. There are 2 exogenous (FARSCH, LOCUS10) and 2 endogenous (T_ATTENT, RMTEST) observed variables in the model. The idea is that T_ATTENT mediates the effect of FARSCH and LOCUS10 on RMTEST. The RAM specification I used is FARSCH - T_ATTENT, y1x1, NA LOCUS10 - T_ATTENT, y1x2, NA FARSCH - RMTEST10, y2x1, NA LOCUS10 - RMTEST10, y2x2, NA T_ATTENT - RMTEST10, y2y1, NA FARSCH - FARSCH, x1x1, NA LOCUS10 - LOCUS10, x2x2, NA T_ATTENT - T_ATTENT, y1y1, NA RMTEST10 - RMTEST10, y2y2, NA LOCUS10 - FARSCH, x2x1, NA This model runs, but using the summary function does not return the usual model fit statistics, only the following: Model Chisquare = 0 Df = 0 Pr(Chisq) = NA Chisquare (null model) = 8526.8 Df = 6 Goodness-of-fit index = 1 BIC = 0 If I omit the last line from the RAM specification(i.e., delete LOCUS10 - FARSCH, x2x1, NA), I DO get 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 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- = David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] No fit statistics for some models using sem
Dear David and Ista, I haven't looked at this model carefully, but the fact that the df are 0 suggests that the model is just-identified and therefore necessarily perfectly reproduces the covariances among the observed variables. Removing a parameter would over-identify the model, making possible the computation of the missing fit statistics. Regards, John On Wed, 7 Mar 2007 18:31:09 + David Barron [EMAIL PROTECTED] wrote: It's not the correlation as such that is the problem; it's because you only have 10 degrees of freedom available with four observed variables, and you are estimating 10 parameters, which is why you get a chi square of zero. When you remove any one free parameter (such as the correlation), the model becomes identified. On 07/03/07, Ista Zahn [EMAIL PROTECTED] wrote: Hi, New to both R and SEM, so this may be a very simple question. I am trying to run a very simple path analysis using the sem package. There are 2 exogenous (FARSCH, LOCUS10) and 2 endogenous (T_ATTENT, RMTEST) observed variables in the model. The idea is that T_ATTENT mediates the effect of FARSCH and LOCUS10 on RMTEST. The RAM specification I used is FARSCH - T_ATTENT, y1x1, NA LOCUS10 - T_ATTENT, y1x2, NA FARSCH - RMTEST10, y2x1, NA LOCUS10 - RMTEST10, y2x2, NA T_ATTENT - RMTEST10, y2y1, NA FARSCH - FARSCH, x1x1, NA LOCUS10 - LOCUS10, x2x2, NA T_ATTENT - T_ATTENT, y1y1, NA RMTEST10 - RMTEST10, y2y2, NA LOCUS10 - FARSCH, x2x1, NA This model runs, but using the summary function does not return the usual model fit statistics, only the following: Model Chisquare = 0 Df = 0 Pr(Chisq) = NA Chisquare (null model) = 8526.8 Df = 6 Goodness-of-fit index = 1 BIC = 0 If I omit the last line from the RAM specification(i.e., delete LOCUS10 - FARSCH, x2x1, NA), I DO get 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 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- = David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. John Fox Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
