[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

From |
Maarten buis <maartenbuis@yahoo.co.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: probit with interaction dummies (significance and marginal effects) |

Date |
Thu, 17 Jul 2008 17:13:47 +0100 (BST) |

Regarding problem 1, this is just a matter of interpretation, as long as you interpret the effects in terms of the effect on the latent variable you are ok in simply using the output from -probit-, if you want to interpret the results in terms of the probability you should use -inteff-. Problem 2 is much harder to solve. Any solution would in one way or another try to controll for things that haven't been observed. It should not come as a surprise that that is hard (read: impossible). So, the fact that "the solution" hasn't been implemented yet in Stata is not so much a problem with Stata but with the state of the statistical science: we know the problem, but we just don't know the answer. Though Rich Williams discusses one solution on his website. -- Maarten --- Andrea Bennett <mac.stata@gmail.com> wrote: > Thanks for the link! Still, I wonder if there's really no Stata > command I could use to "simply" test if the interaction is > significant and what influence (direction) it has on the dependent > variable. I'd be just rather surprised if this does not exist > because it seems to me this is a very common issue in any regression > design (interaction effects). --- Maarten buis wrote: > > There are two distinct issues when interpreting interaction effects > > in a probit: > > > > 1) a significant positive (negative) interaction in terms of the > > latent > > variable does not mean a significant positive (negative) > > interaction effect in terms of the probability that y = 1. > > > > 2) The scale of the latent variable is identified by setting the > > residual variance at 1. If the residual variance differs between > > the groups than that means that the scale of the latent variable > > differs between the groups and when comparing differences in > > effects across the groups you are basically comparing apples and > > oranges. ----------------------------------------- Maarten L. Buis Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands visiting address: Buitenveldertselaan 3 (Metropolitan), room Z434 +31 20 5986715 http://home.fsw.vu.nl/m.buis/ ----------------------------------------- __________________________________________________________ Not happy with your email address?. Get the one you really want - millions of new email addresses available now at Yahoo! http://uk.docs.yahoo.com/ymail/new.html * * 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/

**Follow-Ups**:**Re: st: probit with interaction dummies (significance and marginal effects)***From:*Andrea Bennett <mac.stata@gmail.com>

**References**:**Re: st: probit with interaction dummies (significance and marginal effects)***From:*Andrea Bennett <mac.stata@gmail.com>

- Prev by Date:
**RE: RE : Heteroskedasticity and fixed effects (was: st: RE: Re: Weak instruments)** - Next by Date:
**RE: RE : Heteroskedasticity and fixed effects (was: st: RE: Re: Weak instruments)** - Previous by thread:
**Re: st: probit with interaction dummies (significance and marginal effects)** - Next by thread:
**Re: st: probit with interaction dummies (significance and marginal effects)** - Index(es):

© Copyright 1996–2016 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |