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From |
Huybregts <lievenhu@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Introducing constraints to biprobit model |

Date |
Tue, 28 Aug 2012 17:38:25 +0200 |

Dear Nick, I think there was a misunderstanding. I did post the syntax, but I think you want to see the output. Here is the complete output. First the syntax I have been using, which didn't work, then What Maarten wrote, which is much better. However, I have a remaining question on the r111 error. I don't know if the results obtained by the LR test are correct. Many thanks for any feedback you can provide on this and my apologies for misunderstanding. I did read the rules well to make this as clear as possible. I use Stata 11.1. Lieven First you can see what I have been doing, which didn't work: /*My original synthax */ . sysuse auto.dta,clear (1978 Automobile Data) . egen cat=cut(rep78),grou(2) label (5 missing values generated) . . // model without constraints . xi: biprobit (cat mpg price) (foreign mpg price) Fitting comparison equation 1: Iteration 0: log likelihood = -28.552789 Iteration 1: log likelihood = -27.110671 Iteration 2: log likelihood = -27.076711 Iteration 3: log likelihood = -27.076625 Iteration 4: log likelihood = -27.076625 Fitting comparison equation 2: Iteration 0: log likelihood = -42.400729 Iteration 1: log likelihood = -33.271394 Iteration 2: log likelihood = -33.188125 Iteration 3: log likelihood = -33.188014 Iteration 4: log likelihood = -33.188014 Comparison: log likelihood = -60.26464 Fitting full model: Iteration 0: log likelihood = -60.26464 Iteration 1: log likelihood = -57.973106 Iteration 2: log likelihood = -57.880512 Iteration 3: log likelihood = -57.873467 Iteration 4: log likelihood = -57.873061 Iteration 5: log likelihood = -57.873057 Seemingly unrelated bivariate probit Number of obs = 69 Wald chi2(4) = 14.79 Log likelihood = -57.873057 Prob > chi2 = 0.0052 ------------------------------------------------------------------------------ | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- cat | mpg | .0710587 .0454513 1.56 0.118 -.0180242 .1601416 price | .0000924 .0000748 1.24 0.216 -.0000541 .0002389 _cons | -.9485728 1.211113 -0.78 0.433 -3.322311 1.425166 -------------+---------------------------------------------------------------- foreign | mpg | .140959 .0373519 3.77 0.000 .0677506 .2141674 price | .0001253 .0000681 1.84 0.066 -8.08e-06 .0002588 _cons | -4.377398 1.114323 -3.93 0.000 -6.561432 -2.193365 -------------+---------------------------------------------------------------- /athrho | 1.259137 2.237519 0.56 0.574 -3.12632 5.644595 -------------+---------------------------------------------------------------- rho | .8508261 .6177676 -.9961567 .999975 ------------------------------------------------------------------------------ Likelihood-ratio test of rho=0: chi2(1) = 4.78317 Prob > chi2 = 0.0287 . estimates store R1 . matrix define coef=e(b) . matrix list coef coef[1,7] cat: cat: cat: foreign: foreign: foreign: athrho: mpg price _cons mpg price _cons _cons y1 .07105866 .00009241 -.94857276 .14095901 .00012534 -4.3773984 1.2591375 . constraint define 1 coef[1,1] = coef[1,4] . constraint define 2 coef[1,2] = coef[1,5] . . // Model with constraints . xi: biprobit (cat mpg price) (foreign mpg price), constraint (1 2) Fitting comparison equation 1: (note: constraint number 1 caused error r(131)) (note: constraint number 2 caused error r(131)) Iteration 0: log likelihood = -28.552789 Iteration 1: log likelihood = -27.110671 Iteration 2: log likelihood = -27.076711 Iteration 3: log likelihood = -27.076625 Iteration 4: log likelihood = -27.076625 Fitting comparison equation 2: (note: constraint number 1 caused error r(131)) (note: constraint number 2 caused error r(131)) Iteration 0: log likelihood = -42.400729 Iteration 1: log likelihood = -33.271394 Iteration 2: log likelihood = -33.188125 Iteration 3: log likelihood = -33.188014 Iteration 4: log likelihood = -33.188014 Comparison: log likelihood = -60.26464 Fitting full model: (note: constraint number 1 caused error r(131)) (note: constraint number 2 caused error r(131)) Iteration 0: log likelihood = -60.26464 Iteration 1: log likelihood = -57.973106 Iteration 2: log likelihood = -57.880512 Iteration 3: log likelihood = -57.873467 Iteration 4: log likelihood = -57.873061 Iteration 5: log likelihood = -57.873057 Seemingly unrelated bivariate probit Number of obs = 69 Wald chi2(4) = 14.79 Log likelihood = -57.873057 Prob > chi2 = 0.0052 ------------------------------------------------------------------------------ | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- cat | mpg | .0710587 .0454513 1.56 0.118 -.0180242 .1601416 price | .0000924 .0000748 1.24 0.216 -.0000541 .0002389 _cons | -.9485728 1.211113 -0.78 0.433 -3.322311 1.425166 -------------+---------------------------------------------------------------- foreign | mpg | .140959 .0373519 3.77 0.000 .0677506 .2141674 price | .0001253 .0000681 1.84 0.066 -8.08e-06 .0002588 _cons | -4.377398 1.114323 -3.93 0.000 -6.561432 -2.193365 -------------+---------------------------------------------------------------- /athrho | 1.259137 2.237519 0.56 0.574 -3.12632 5.644595 -------------+---------------------------------------------------------------- rho | .8508261 .6177676 -.9961567 .999975 ------------------------------------------------------------------------------ Likelihood-ratio test of rho=0: chi2(1) = 4.78317 Prob > chi2 = 0.0287 . estimates store R2 . lrtest R1 R2 df(unrestricted) = df(restricted) = 7 r(498); end of do-file Here you can see what Maarten proposed in his previous posting, my question is how to interpret the (note: constraint number 2 caused error r(111)). . /* Maarten's proposal */ . sysuse auto.dta,clear (1978 Automobile Data) . egen cat=cut(rep78),grou(2) label (5 missing values generated) . . // model without constraints . biprobit (cat mpg price) /// > (foreign mpg price) Fitting comparison equation 1: Iteration 0: log likelihood = -28.552789 Iteration 1: log likelihood = -27.110671 Iteration 2: log likelihood = -27.076711 Iteration 3: log likelihood = -27.076625 Iteration 4: log likelihood = -27.076625 Fitting comparison equation 2: Iteration 0: log likelihood = -42.400729 Iteration 1: log likelihood = -33.271394 Iteration 2: log likelihood = -33.188125 Iteration 3: log likelihood = -33.188014 Iteration 4: log likelihood = -33.188014 Comparison: log likelihood = -60.26464 Fitting full model: Iteration 0: log likelihood = -60.26464 Iteration 1: log likelihood = -57.973106 Iteration 2: log likelihood = -57.880512 Iteration 3: log likelihood = -57.873467 Iteration 4: log likelihood = -57.873061 Iteration 5: log likelihood = -57.873057 Seemingly unrelated bivariate probit Number of obs = 69 Wald chi2(4) = 14.79 Log likelihood = -57.873057 Prob > chi2 = 0.0052 ------------------------------------------------------------------------------ | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- cat | mpg | .0710587 .0454513 1.56 0.118 -.0180242 .1601416 price | .0000924 .0000748 1.24 0.216 -.0000541 .0002389 _cons | -.9485728 1.211113 -0.78 0.433 -3.322311 1.425166 -------------+---------------------------------------------------------------- foreign | mpg | .140959 .0373519 3.77 0.000 .0677506 .2141674 price | .0001253 .0000681 1.84 0.066 -8.08e-06 .0002588 _cons | -4.377398 1.114323 -3.93 0.000 -6.561432 -2.193365 -------------+---------------------------------------------------------------- /athrho | 1.259137 2.237519 0.56 0.574 -3.12632 5.644595 -------------+---------------------------------------------------------------- rho | .8508261 .6177676 -.9961567 .999975 ------------------------------------------------------------------------------ Likelihood-ratio test of rho=0: chi2(1) = 4.78317 Prob > chi2 = 0.0287 . estimates store R1 . . // replay the model, but see the coefficient names: . biprobit, coeflegend Seemingly unrelated bivariate probit Number of obs = 69 Wald chi2(4) = 14.79 Log likelihood = -57.873057 Prob > chi2 = 0.0052 ------------------------------------------------------------------------------ | Coef. Legend -------------+---------------------------------------------------------------- cat | mpg | .0710587 _b[cat:mpg] price | .0000924 _b[cat:price] _cons | -.9485728 _b[cat:_cons] -------------+---------------------------------------------------------------- foreign | mpg | .140959 _b[foreign:mpg] price | .0001253 _b[foreign:price] _cons | -4.377398 _b[foreign:_cons] -------------+---------------------------------------------------------------- /athrho | 1.259137 _b[athrho:_cons] -------------+---------------------------------------------------------------- rho | .8508261 ------------------------------------------------------------------------------ Likelihood-ratio test of rho=0: chi2(1) = 4.78317 Prob > chi2 = 0.0287 . . // use those name to define the constraints . constraint define 1 _b[cat:mpg] = _b[foreign:mpg] . constraint define 2 _b[cat:price] = _b[foreign:price] . . // Model with constraints . biprobit (cat mpg price) /// > (foreign mpg price), constraint (1 2) Fitting comparison equation 1: (note: constraint number 1 caused error r(111)) (note: constraint number 2 caused error r(111)) Iteration 0: log likelihood = -28.552789 Iteration 1: log likelihood = -27.110671 Iteration 2: log likelihood = -27.076711 Iteration 3: log likelihood = -27.076625 Iteration 4: log likelihood = -27.076625 Fitting comparison equation 2: (note: constraint number 1 caused error r(111)) (note: constraint number 2 caused error r(111)) Iteration 0: log likelihood = -42.400729 Iteration 1: log likelihood = -33.271394 Iteration 2: log likelihood = -33.188125 Iteration 3: log likelihood = -33.188014 Iteration 4: log likelihood = -33.188014 Comparison: log likelihood = -60.26464 Fitting full model: Iteration 0: log likelihood = -83.049875 Iteration 1: log likelihood = -65.030586 (not concave) Iteration 2: log likelihood = -59.728978 Iteration 3: log likelihood = -58.803484 Iteration 4: log likelihood = -58.800879 Iteration 5: log likelihood = -58.800664 Iteration 6: log likelihood = -58.800664 Seemingly unrelated bivariate probit Number of obs = 69 Wald chi2(2) = 14.07 Log likelihood = -58.800664 Prob > chi2 = 0.0009 ( 1) [cat]mpg - [foreign]mpg = 0 ( 2) [cat]price - [foreign]price = 0 ------------------------------------------------------------------------------ | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- cat | mpg | .1214969 .0324577 3.74 0.000 .057881 .1851127 price | .0001177 .0000556 2.12 0.034 8.82e-06 .0002267 _cons | -2.072698 .8765444 -2.36 0.018 -3.790693 -.3547025 -------------+---------------------------------------------------------------- foreign | mpg | .1214969 .0324577 3.74 0.000 .057881 .1851127 price | .0001177 .0000556 2.12 0.034 8.82e-06 .0002267 _cons | -3.888234 .9489108 -4.10 0.000 -5.748065 -2.028403 -------------+---------------------------------------------------------------- /athrho | 1.776488 175.2688 0.01 0.992 -341.744 345.2969 -------------+---------------------------------------------------------------- rho | .9443162 18.97581 -1 1 ------------------------------------------------------------------------------ Likelihood-ratio test of rho=0: chi2(1) = 2.92795 Prob > chi2 = 0.0871 . estimates store R2 . lrtest R1 R2 Likelihood-ratio test LR chi2(2) = 1.86 (Assumption: R2 nested in R1) Prob > chi2 = 0.3955 . end of do-file On Aug 28, 2012, at 3:35 PM, Nick Cox wrote: > There is plenty of good will to help you, but there is no way round > this: you have yet to post the entire syntax that you used. So I don't > think anyone can see what you are doing wrong even in trying to > reproduce Maarten's example. This logic should seem compelling even to > first-time posters. > > Nick > > On Tue, Aug 28, 2012 at 12:50 PM, Huybregts <lievenhu@gmail.com> wrote: >> Nick, you're quite right, it' s the first time I post here, thought it would add my first message as well. >> Maarten corrected mistakes in my original coding (so that's solved). My remaining question is regarding the code he proposed. >> >> If I run Maarten's code, for the "model with constraints" (biprobit (cat mpg price) (foreign mpg price), constraint (1 2), >> I get the error message: >> (note: constraint number 1 caused error r(111)) ( no variables defined;) >> (note: constraint number 2 caused error r(111)) >> It does not seem to accept the constraints, but runs the full model nevertheless. Can I assume for this that since the constraints entail coefficients from both models, when stata runs model 1 and model 2 separately it cannot apply the constraints because they are not known yet (seems logic enough). Just to be sure. The LR test gives results do I assume that stata acknowledged the constraints (as difference in df). >> >> Thanks for your help and sorry for the mess, >> Lieven >> >> >> >> On Aug 28, 2012, at 11:29 AM, Nick Cox wrote: >> >>> Asking this question without showing what you typed wastes everybody's time. >>> >>> What is the entire and exact syntax that you typed? >>> >>> Can you reproduce Maarten's example? What is different about what you typed. >>> >>> Nick >>> >>> On Tue, Aug 28, 2012 at 10:29 AM, Huybregts <lievenhu@gmail.com> wrote: >>>> Many thanks for the reply and the coding Maarten, however if I run the model with constraints, I get the error message: >>>> (note: constraint number 1 caused error r(111)) ( no variables defined;) >>>> (note: constraint number 2 caused error r(111)) >>>> >>>> It does not seem to accept the constraints, but runs the full model nevertheless. Can I assume for this that since the constraints entail coefficients from both models, when stata runs model 1 and model 2 separately it cannot apply the constraints because they are not known yet (seems logic enough). Just to be sure. >>>> Cheers, >>>> >>>> Lieven >>>> >>>> >>>> >>>> >>>> On Aug 28, 2012, at 11:05 AM, Maarten Buis wrote: >>>> >>>>> sysuse auto.dta,clear >>>>> egen cat=cut(rep78),grou(2) label >>>>> >>>>> // model without constraints >>>>> biprobit (cat mpg price) /// >>>>> (foreign mpg price) >>>>> estimates store R1 >>>>> >>>>> // replay the model, but see the coefficient names: >>>>> biprobit, coeflegend >>>>> >>>>> // use those name to define the constraints >>>>> constraint define 1 _b[cat:mpg] = _b[foreign:mpg] >>>>> constraint define 2 _b[cat:price] = _b[foreign:price] >>>>> >>>>> // Model with constraints >>>>> biprobit (cat mpg price) /// >>>>> (foreign mpg price), constraint (1 2) >>>>> estimates store R2 >>>>> lrtest R1 R2 >> >> >> >>>> On Aug 28, 2012, at 10:05 AM, Huybregts wrote: >> <Dear Stata listers, >> < >> <To test if two binary outcomes have the same underlying pattern of predictors, we compared 2 biprobit models (one with constraints, one without) using a LR test. However we encounter a <recurring error for which we can't find a solution. To make this understandable I use the auto.dta dataset to replicate our problem from a different dataset. >> < >> <************************************************ >> sysuse auto.dta,clear >> egen cat=cut(rep78),grou(2) label >> >> * model without constraints >> xi: biprobit (cat mpg price) (foreign mpg price) >> estimates store R1 >> matrix define coef=e(b) >> matrix list coef >> constraint define 1 coef[1,1] = coef[1,4] >> constraint define 2 coef[1,2] = coef[1,5] >> >> * Model with constraints >> xi: biprobit (cat mpg price) (foreign mpg price), constraint (1 2) >> estimates store R2 >> lrtest R1 R2 >> <************************************************ >> <The error I get is (just after the model with constraints) >> < >> <Fitting comparison equation 1: >> <(note: constraint number 1 caused error r(131)) >> <(note: constraint number 2 caused error r(131)) >> < >> <I did not find a similar problem on the statalist, would it be impossible for the biprobit to converge adding constraints of equal coefficients? >> <I use Stata 11.1. >> <Many thanks for any help anyone could provide. >> < > > * > * 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/

**Follow-Ups**:**Re: st: Introducing constraints to biprobit model***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**st: Introducing constraints to biprobit model***From:*Huybregts <lievenhu@gmail.com>

**Re: st: Introducing constraints to biprobit model***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: Introducing constraints to biprobit model***From:*Huybregts <lievenhu@gmail.com>

**Re: st: Introducing constraints to biprobit model***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Introducing constraints to biprobit model***From:*Huybregts <lievenhu@gmail.com>

**Re: st: Introducing constraints to biprobit model***From:*Nick Cox <njcoxstata@gmail.com>

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