You are making life very complicated for yourself and your
audience: your odds ratio will now depend on at what value
of wage and at what value of grade you evaluate your
equation. So you will need to present a two-dimensional
table to accurately display the effect-size.
The computation is in principle not hard, but it is very
easy to get confused. It is just a matter of writing down
the equation and go step by step through the logic of an
interaction effect. However, I am in a hotel right now, so
I don't have access to my whiteboard, so I will not even
attempt to solve that problem.
I would just present the graphs I gave you in my first
post, they are going to be a much clearer presentation of
your results than the two-dimensional table you would
need to produce if you want to present them numerically.
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
--- On Mon, 3/8/09, Pabst Alexander <[email protected]> wrote:
> From: Pabst Alexander <[email protected]>
> Subject: AW: AW: st: logit with interaction and transformation
> To: [email protected]
> Date: Monday, 3 August, 2009, 12:52 PM
> Great. This is a step closer to the
> solution.
>
> But I actually want the odds ratios of the (ln transformed)
> independent variable at different values of the
> (non-transformed) moderator, i.e. just the other way
> around.
> To stay at your example, that would mean want I want the
> odds ratios of grade when at different values of wage. Would
> it then read like this below?
> But this yields big ORs, so I assume there`s still a
> mistake in!?
>
> Alex
>
> *--------------------- begin example ------------------
> gen lngrade = ln(grade)
> gen wageXlngrade = wage*lngrade
>
> logit union lngrade wage wageXlngrade married
> never_married, or
>
> sum wage if e(sample)
> global m = r(mean)
> global sd = r(sd)
>
> nlcom (mean_minus_1sd:
>
> ///
> exp( (exp(_b[lngrade]))
> +
> ///
>
> ($m-$sd)*_b[wageXlngrade] )
> ) ///
> (mean:
>
>
> ///
> exp( (exp(_b[lngrade]))
> +
> ///
>
> ($m)*_b[wageXlngrade] ) )
> ///
> (mean_plus_1sd:
>
> ///
> exp( (exp(_b[lngrade]))
> +
> ///
>
> ($m+$sd)*_b[wageXlngrade] ) )
> *--------------------- end example --------------------
>
>
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> [mailto:[email protected]]
> Im Auftrag von Maarten buis
> Gesendet: Montag, 3. August 2009 13:03
> An: [email protected]
> Betreff: Re: AW: st: logit with interaction and
> transformation
>
>
> --- On Mon, 3/8/09, Pabst Alexander wrote:
> > But just for the case: would it be correct to
> calculate
> > either
> > Y= X1 + (ln)X2 + X1*(ln)X2
> > sum X1
> > global m = r(mean)
> > global sd = r(sd)
> >
> > (1) nlcom exp(x2) +
> ($m+$sd)*X2*X1
> > or (2) nlcom exp(x2) +
> > exp(($m+$sd)*X2*X1)
> >
> > Or would I have to manage this somehow in terms of
> marginal
> > effects, e.g.
> > mfx, eydx at(X1=$m)?
>
> None of these would be correct. Apparently (in terms of the
>
> example below) you want the odds ratios of south when at
> different values of grade. Below I picked the numbers
> mean grade - 1 sd, mean grade, and mean + 1 sd. Notice that
>
> I used the mean and standard deviation of grade and only
> later transformed it into ln(grade), as this way your
> interpretation will accept the unit of measurement of grade
>
> rather than ln(grade).
>
> *--------------------- begin example ------------------
> sysuse nlsw88, clear
> gen lngrade = ln(grade)
> gen southXlngrade = south*lngrade
> logit union lngrade south southXlngrade ///
> married
> never_married, or
>
> sum grade if e(sample)
> local m = r(mean)
> local sd = r(sd)
>
> nlcom (mean_minus_1sd:
>
> ///
> exp( _b[south] +
>
> ///
>
> ln(`m'-`sd')*_b[southXlngrade] ) ) ///
> (mean:
>
>
> ///
> exp( _b[south] +
>
> ///
>
> ln(`m')*_b[southXlngrade] ) )
> ///
> (mean_plus_1sd:
>
> ///
> exp( _b[south] +
>
> ///
>
> ln(`m'+`sd')*_b[southXlngrade] ) )
>
> *--------------------- end example --------------------
>
> Hope this helps,
> Maarten
>
> -----------------------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
>
>
>
>
>
>
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