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From |
Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: AW: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step |

Date |
Sun, 18 Jul 2010 02:18:43 +0530 |

No, you are right. Just updated the ado from SSC (5th April version to 5th July). It is broken. T 2010/7/18 Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com>: > Martin, > > That example runs without problems. You might want to try > > mata: mata mlib index > > before you run that example. > > T > > > 2010/7/18 Martin Weiss <martin.weiss1@gmx.de>: >> >> <> >> >> >> " However, the following syntax >> >> xi: cmp (y1 = x1) (y2 = x2 y1), ind(5 1)" >> >> >> >> What is -xi- good for in your -cmp- call, btw? >> >> >> >> HTH >> Martin >> >> >> -----Ursprüngliche Nachricht----- >> Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von ??? >> Gesendet: Samstag, 17. Juli 2010 22:17 >> An: "Martin Weiss" >> Cc: statalist@hsphsun2.harvard.edu >> Betreff: st: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step >> >> Dear Martin, >> >> Thanks for your comment. >> It was helpful. >> >> However, the following syntax >> >> xi: cmp (y1 = x1) (y2 = x2 y1), ind(5 1) >> >> where y1 = ordinal numbers like 1, 2, 3, 4 >> y2 = continuous >> >> gives an error sign like "matrix___00000B not found" >> >> And the program shows (y1 = x1) result only, which is exactly identical to >> the outcome from an (oprobit y1 x1) regression. >> >> Thanks in advance. >> >> Jaemin >> >> >> >> >> >> ----- Original Message ----- >> From: "Martin Weiss" <martin.weiss1@gmx.de> >> To: <statalist@hsphsun2.harvard.edu> >> Sent: Saturday, July 17, 2010 10:45 PM >> Subject: st: AW: treatment effect estimation with an ordinal 1st step and a >> continuous 2nd step >> >> >>> >>> <> >>> >>> Try >>> >>> ************* >>> ssc d cmp >>> ************* >>> >>> >>> >>> HTH >>> Martin >>> >>> -----Ursprüngliche Nachricht----- >>> Von: owner-statalist@hsphsun2.harvard.edu >>> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von ??? >>> Gesendet: Samstag, 17. Juli 2010 15:29 >>> An: statalist@hsphsun2.harvard.edu >>> Betreff: st: treatment effect estimation with an ordinal 1st step and a >>> continuous 2nd step >>> >>> Hi all! >>> >>> I want to run a treatment effects model. >>> >>> In my case, the 1st step dependent var. is ordinal (for exmaple, >>> "perfectly >>> not matched", "not matched", "matched", and "perfectly matched"), and the >>> 2nd step dependent var. is continuous (for example, wage in log). >>> I have run the similar model using "treatreg" command if the 1st step >>> depednat is binary. >>> >>> Is there any command working in this case. >>> >>> I found "mtreatreg" is available if >>> (1) 1st step dependent var. is multivariate and >>> (2) 2nd step DV is continuous >>> >>> Of course, 1st step ordinal treatment variable should be shown in the 2nd >>> step equation as an independent variable explicitly. >>> >>> P.S.: I don't think running "oprobit" as the 1st step, and insertting IMR >>> from it as independent variable into the 2nd step OLS regression is valid. >>> >>> Thanks, >>> jaemin >>> >>> * >>> * 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/ >>> >>> >> >> >> * >> * 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/ >> > > > > -- > 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). > -- 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/

**References**:**st: treatment effect estimation with an ordinal 1st step and a continuous 2nd step***From:*박재민 <jaeminpark1@gmail.com>

**st: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step***From:*박재민 <jpark@konkuk.ac.kr>

**Re: st: AW: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step***From:*Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com>

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