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From |
"JVerkuilen (Gmail)" <jvverkuilen@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Hierarchical CFA problem |

Date |
Mon, 22 Apr 2013 11:07:00 -0400 |

On Mon, Apr 22, 2013 at 10:33 AM, John Antonakis <John.Antonakis@unil.ch> wrote: > BTW, by "look at your output," I meant when you force Stata to stop > iterating: > > -------------+---------------------------------------------------------------- > Variance | > e.x1 | .5509189 .1985341 .2718573 1.116437 > e.x2 | 1.086973 .1179499 .8787249 1.344574 > e.x3 | .8554162 .1292344 .6361797 1.150205 > e.x4 | .345022 .0468115 .264459 .4501272 > e.x5 | .4623856 .0608402 .3572761 .5984178 > e.x6 | .3636892 .0440637 .2868144 .4611688 > e.x7 | .5784454 .110548 .3977291 .8412739 > e.x8 | .5318421 .0899317 .3818115 .7408264 > e.x9 | .7004508 .0882214 .5472292 .8965738 > e.L1 | -1.00e-09 .2417215 . . > e.L2 | .9446486 .1340474 .7152918 1.247548 > e.L3 | .5939406 .1637864 .3459504 1.0197 > G | .7258514 .2259537 .3943421 1.336049 > ------------------------------------------------------------------------------ > > In any case, the chi-square overidentification test shows that this model is > no good. Yes, it's a Heywood case in latent variable L1. lavaan was heading to it but didn't quite get there. That can happen with different estimation algorithms. This model is not properly specified and given that it's not regular any chi square statistics for it are misleading. One of the surest signs in standard output is a variance parameter that is about the same size as its standard error, and the point estimate for e.L1 here is clearly numerically 0 (negative only due to rounding error). The only way that can possibly happen is when the likelihood for that parameter is piling up on 0. A variance parameter's log-likelihood should be essentially the same shape as that of a chi square distribution's. When the DF gets very low the chi square is substantially right-skewed and eventually has a mode at 0. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: Hierarchical CFA problem***From:*John Antonakis <John.Antonakis@unil.ch>

**Re: st: Hierarchical CFA problem***From:*John Antonakis <John.Antonakis@unil.ch>

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