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From |
m.spitzenpfeil@gmx.net |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: GLLAMM: Predict Class Membership |

Date |
Wed, 19 Sep 2012 14:13:03 +0200 |

probabilities of belonging to the class (class 1 instead of 0). Since there are only two classes i expected the mean of the class variable to equal the prior probability of belonging to class 1. That's not the case, though. Thanks for the references! Martin Am 19.09.2012 14:05, schrieb Cameron McIntosh:

You will often see people assigning cases to classes based on posterior probabilities (usually to run separate logistic regressions of classes on covariates), but this removes uncertainty in class membership and thus biases standard errors of coefficients downward. So optimally you would use a concomitant-variable LCA, or improved multi-step approaches: Vermunt, J.K. (2010). Latent Class Modeling with Covariates: Two Improved Three-Step Approaches. Political Analysis, 18(4), 450-469. Clark, S. & Muthén, B. (submitted). Relating latent class analysis results to variables not included in the analysis. http://www.statmodel.com/download/relatinglca.pdf CamDate: Wed, 19 Sep 2012 12:34:42 +0200 From: m.spitzenpfeil@gmx.net To: statalist@hsphsun2.harvard.edu Subject: st: GLLAMM: Predict Class Membership Hi, is there any way to predict individual latent class membership as a dummy variable - and not in terms of probability - using GLLAMM? My modell is structurally equivalent to the Myocardial Infarction Example: http://www.gllamm.org/examples.html http://www.gllamm.org/data_dofile.zip insheet using mi.dat, clear rename q y1 rename h y2 rename l y3 rename c y4 gen wt2 = count gen patt=_n reshape long y, i(patt) j(var) tab var, gen(v) eq v1: v1 eq v2: v2 eq v3: v3 eq v4: v4 gllamm y, i(patt) ip(fn) nip(2) eqs(v1 v2 v3 v4) /* */ weight(wt) nrf(4) l(logit) f(binom) nocons Thanks for your help! Martin * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: GLLAMM: Predict Class Membership***From:*m.spitzenpfeil@gmx.net

**RE: st: GLLAMM: Predict Class Membership***From:*Cameron McIntosh <cnm100@hotmail.com>

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