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From |
Benjamin Niug <benjamin.niug@googlemail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Binary Choice Model and fixed effects - interpreting the interaction effects? |

Date |
Mon, 2 Apr 2012 16:18:30 +0200 |

@Maarten. Thanks again. Am 2. April 2012 16:00 schrieb Maarten Buis <maartenlbuis@gmail.com>: > That is due to the effect of that the constant is not calculated in > these models. So you'll have to interpret the odds ratios without the > baseline odds. This is not ideal but can be done, and I guess that is > the price you'll have to pay for estimating a fixed effects model... > > -- Maarten > > On Mon, Apr 2, 2012 at 3:39 PM, Benjamin Niug wrote: >> Maarten - thanks a lot for clarification. >> >> In case of a clogit xtlogit, the baseline-trick you applied, namely >> generating a variable >> >> gen baseline = 1 >> >> and then running the logit-regression also on baseline such that the >> odds ratios of the interaction effect can be compared to the baseline >> odds ratio does not work due to multicollinearity of the baseline >> variable. >> >> How do I solve this problem? I guess a constant could serve the same >> purpose as your baseline variable - however it is not reported >> neither. How do I still come up with a meaningful interpretation? >> >> Many thanks in advance. >> >> >> Am 2. April 2012 15:17 schrieb Maarten Buis <maartenlbuis@gmail.com>: >>> On Mon, Apr 2, 2012 at 2:37 PM, Benjamin Niug wrote: >>>> @Maarten. Thanks. I tried to calculated the marginal effects as >>>> indicated in the paper you mentioned (M.L. Buis (2010) "Stata tip 87: >>>> Interpretation of interactions in non-linear models", The Stata >>>> Journal, 10(2), pp. 305-308) >>>> >>>> However, some interactions are not estimated / "estimable" by Stata >>>> using the -margins- command. >>> >>> The point of that article is that you should _not_ estimate marginal >>> effects. In that article I tried to be nice towards Edward Norton and >>> colleagues and tried to find some situation where marginal effects >>> might make some sense. I did find such a special situation in the case >>> of a fully saturated model(*), but in practice you should just forget >>> about that and go for odds ratios. In retrospect that inclusion of >>> marginal effects in the article was a mistake as this confuses more >>> than it helps. >>> >>> So the bottom line is: There is only one solution and that is to >>> interpret the results in terms of odds ratios. >>> >>> Hope this helps, >>> Maarten >>> >>> (*) A fixed effects model with covariates cannot be a fully saturated >>> model, so this is not an "escape route" open to you. You really really >>> really have no other option than to learn how to use and report odds, >>> odds ratios and ratios of odds ratios. >>> >>> >>> >>> -------------------------- >>> Maarten L. Buis >>> Institut fuer Soziologie >>> Universitaet Tuebingen >>> Wilhelmstrasse 36 >>> 72074 Tuebingen >>> Germany >>> >>> >>> http://www.maartenbuis.nl >>> -------------------------- >>> * >>> * 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/ > > > > -- > -------------------------- > Maarten L. Buis > Institut fuer Soziologie > Universitaet Tuebingen > Wilhelmstrasse 36 > 72074 Tuebingen > Germany > > > http://www.maartenbuis.nl > -------------------------- > > * > * 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: Binary Choice Model and fixed effects - interpreting the interaction effects?***From:*Benjamin Niug <benjamin.niug@googlemail.com>

**Re: st: Binary Choice Model and fixed effects - interpreting the interaction effects?***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: Binary Choice Model and fixed effects - interpreting the interaction effects?***From:*Benjamin Niug <benjamin.niug@googlemail.com>

**Re: st: Binary Choice Model and fixed effects - interpreting the interaction effects?***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: Binary Choice Model and fixed effects - interpreting the interaction effects?***From:*Benjamin Niug <benjamin.niug@googlemail.com>

**Re: st: Binary Choice Model and fixed effects - interpreting the interaction effects?***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: Binary Choice Model and fixed effects - interpreting the interaction effects?***From:*Benjamin Niug <benjamin.niug@googlemail.com>

**Re: st: Binary Choice Model and fixed effects - interpreting the interaction effects?***From:*Maarten Buis <maartenlbuis@gmail.com>

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