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From |
<I.Roland@lse.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: AW: computing interaction effects after xtprobit |

Date |
Tue, 31 Mar 2009 12:05:38 +0100 |

Hi Martin/Austin Thanks for this. I am trying to replicate what -inteff- does with -predictnl- for my model. My variables are as follows: y binary dependent variable cont1 continuous independent variable cont2 continuous independent variable inter: cont1*cont2 cont3 continuous independent variable The RE probit is: xtprobit y cont1 cont2 inter cont3, i(group) Based on Norton and Ai (2004, p.158), I then use the following code to compute the interaction effect: local xb = _b[_cons] + _b[cont1]*cont1 + _b[cont2]*cont2 + _b[inter]*inter + _b[cont3]*cont3 local coef = _b[inter] - (_b[cont1]+_b[inter]*cont2)*(_b[cont2] + _b[inter]*cont1)*(_b[_cons] + _b[cont1]*cont1 +_b[cont2]*cont2 + _b[inter]*inter + _b[cont3]*cont3) predictnl interac = (`coef')*(normden(`xb')), se(se_interac) sum interac se_interac That runs fine but delivers a constant interaction effect. Forgive my ignorance, but could this be because it ignores the unobserved random effects? Alternatively, I would like to estimate a FE probit - same model as above but with indicator variables (identified by group in the RE model). This approach may be better since it is not possible to capture the unobserved random effects. I have a lot of indicator variables and would like to find an easy way to capture them in the code that I need to run to compute the interaction effect. It seems it is not possible to use the usual truncation * in the code (see code I tried below where ind* captures all the indicators). local xb = _b[_cons] + _b[cps]*cps + _b[rz]*rz + _b[cpsrz]*cpsrz + _b[share]*share + _b[ind*]*(ind*) Thanks a lot for your advice! ________________________________ From: owner-statalist@hsphsun2.harvard.edu on behalf of Martin Weiss Sent: Fri 27/03/2009 17:07 To: statalist@hsphsun2.harvard.edu Subject: st: AW: computing interaction effects after xtprobit <> http://www.stata-journal.com/sjpdf.html?articlenum=st0063, page 156 says that you can replicate anything -ssc d inteff- does via -predictnl-. HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von I.Roland@lse.ac.uk Gesendet: Freitag, 27. März 2009 18:02 An: statalist@hsphsun2.harvard.edu Betreff: st: computing interaction effects after xtprobit Hello Statalisters, I would like to estimate a random-effects probit that includes an interaction term between two continuous independent variables. After the command 'probit', 'inteff' can be used to compute the correct interaction effects. However, it does not seem to work after 'xtprobit'. Does anyone know how to compute interaction effects after 'xtprobit'? Thanks in advance! Please access the attached hyperlink for an important electronic communications disclaimer: http://www.lse.ac.uk/collections/secretariat/legal/disclaimer.htm * * 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/ Please access the attached hyperlink for an important electronic communications disclaimer: http://www.lse.ac.uk/collections/secretariat/legal/disclaimer.htm

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**Follow-Ups**:**st: AW: RE: AW: computing interaction effects after xtprobit***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**st: AW: RE: AW: computing interaction effects after xtprobit***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**References**:**st: computing interaction effects after xtprobit***From:*<I.Roland@lse.ac.uk>

**st: AW: computing interaction effects after xtprobit***From:*"Martin Weiss" <martin.weiss1@gmx.de>

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