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From |
Tirthankar Chakravarty <[email protected]> |

To |
[email protected] |

Subject |
Re: Re: Re: st: 'margin' and marg. effects of second-order polynomials |

Date |
Wed, 29 Dec 2010 16:31:38 -0800 |

Yes, those two approaches are equivalent. You can see this by constructing the example on page 979 of the manual [R] both ways - exactly the same model is computed in both cases. ********************************************** use http://www.stata-press.com/data/r11/margex, clear logistic outcome treatment##group age c.age#c.age margins, dydx(age) logistic outcome treatment##group c.age##c.age margins, dydx(age) ********************************************** T On Wed, Dec 29, 2010 at 4:18 PM, Justina Fischer <[email protected]> wrote: > even is there was a difference, > > c.mpg#c.mpg = x^2 > > what about the x then ? (my function is F = ax + bx^2 ) > > would your approach work if you estimated (two #) : > > oprobit rep77 foreign length c.mpg##c.mpg > foreach i of numlist `replev' { > > margins, dydx(mpg) predict(outcome(`i')) > > would you get the overall dF/dx ? > > > > > > [email protected] schrieb: ----- > > An: [email protected] > Von: Tirthankar Chakravarty <[email protected]> > Gesendet von: [email protected] > Datum: 30.12.2010 01:12AM > Thema: Re: Re: st: 'margin' and marg. effects of second-order polynomials > > Justina, > > Try this code to see the difference between the two methods of > calculating the marginal effects: > ******************************************************** > webuse fullauto, clear > levelsof rep77, local(replev) > > // higher-order term not included > oprobit rep77 foreign length mpg > foreach i of numlist `replev' { > margins, dydx(mpg) predict(outcome(`i')) > } > > // include as continuous interactions > oprobit rep77 foreign length c.mpg#c.mpg > foreach i of numlist `replev' { > margins, dydx(mpg) predict(outcome(`i')) > } > > // include explicitly > g mpgsq = mpg^2 > oprobit rep77 foreign length mpg mpgsq > foreach i of numlist `replev' { > margins, dydx(mpg mpgsq) predict(outcome(`i')) > } > ******************************************************** > > T > > > On Wed, Dec 29, 2010 at 3:57 PM, Justina Fischer <[email protected]> wrote: >> Yes, I did - the x is continuous (so I used c.x##c.x). >> >> I then used >> margin, dydx(x) >> >> Nevertheless, checking the marginal effects against a naive specification >> (x >> and x^2) I seemed to get the same marginal effects of x as before again ? >> >> Justina >> >> >> >> [email protected] schrieb: ----- >> >> An: [email protected] >> Von: Tirthankar Chakravarty <[email protected]> >> Gesendet von: [email protected] >> Datum: 30.12.2010 12:53AM >> Thema: Re: st: 'margin' and marg. effects of second-order polynomials >> >> Use continuous interactions: >> >> ************************************* >> webuse fullauto, clear >> oprobit rep77 foreign length c.mpg#c.mpg >> margins, dydx(mpg) >> ************************************* >> >> T >> >> On Wed, Dec 29, 2010 at 3:30 PM, Justina Fischer <[email protected]> wrote: >>> Hi >>> >>> I am estimating (using oprobit, unfortunately) a functional relationship >>> of >>> the following kind (simplified) >>> >>> Pr(F) = ax + bx^2 + other stuff. >>> >>> I am interested in the marginal effect: dPr(F)/dx = a + 2bx >>> >>> Using margin, I get marginal effects as if x and x^2 were two separate >>> variables, even though I interact the factor x (x##x) in my >>> specification. >>> >>> Is there a way to make 'margin' estimate dPr(F)/dx, taking into account >>> the >>> functional relationship ? >>> >>> Browsing the Stata archive did not help....and calculating by hand is >>> probably rather unfeasible. >>> >>> Thanks >>> >>> Justina >> >> >> >> -- >> To every ω-consistent recursive class κ of formulae there >> correspond >> recursive class signs r, such that neither v Gen r nor Neg(v Gen r) >> belongs to Flg(κ) (where v is the free variable of r). >> >> * >> * 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/ >> >> > > > > -- > To every ω-consistent recursive class κ of formulae there > correspond > recursive class signs r, such that neither v Gen r nor Neg(v Gen r) > belongs to Flg(κ) (where v is the free variable of r). > > * > * 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/ > > -- To every ω-consistent recursive class κ of formulae there correspond recursive class signs r, such that neither v Gen r nor Neg(v Gen r) belongs to Flg(κ) (where v is the free variable of r). * * 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**:**Antwort: Re: Re: Re: st: 'margin' and marg. effects of second-order polynomials***From:*Justina Fischer <[email protected]>

**References**:**st: 'margin' and marg. effects of second-order polynomials***From:*Justina Fischer <[email protected]>

**Re: st: 'margin' and marg. effects of second-order polynomials***From:*Tirthankar Chakravarty <[email protected]>

**Antwort: Re: st: 'margin' and marg. effects of second-order polynomials***From:*Justina Fischer <[email protected]>

**Re: Re: st: 'margin' and marg. effects of second-order polynomials***From:*Tirthankar Chakravarty <[email protected]>

**Antwort: Re: Re: st: 'margin' and marg. effects of second-order polynomials***From:*Justina Fischer <[email protected]>

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