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From |
"Clive Nicholas" <[email protected]> |

To |
[email protected] |

Subject |
st: Adding -nocons- to -mlbeta- |

Date |
Tue, 24 May 2005 20:48:18 +0100 (BST) |

All, Hello again! Nice to be back... I have a query about a user-written program called -mlbeta-, which runs maximum-likelihood beta-distributed regression models. These models have been shown to be sometimes more suitable than OLS models when the response variable is a proportion between 0 and 1 (Paolino 2001). They model the impact of the control variables not just on the mean of the response, but also on its variance. If you're not familar with it, the code is presented below: program define mlbeta, rclass version 8 syntax varlist [if][in] [,DIspersion(varlist)] [,Robust] [,svy] [,nocons] tokenize `varlist' marksample touse if "`svy'"!=""{ svymarkout `touse' } local lhs "`1'" mac shift local rhs "`*'" ml model lf mlbeta_ll (`lhs'=`rhs') (`dispersion') `if' `in', `robust' `svy' `nocons' ml search ml maximize tempvar error quietly { predict `error' if e(sample) replace `error' = exp(`error')/(1+exp(`error')) replace `error' = (`lhs' - `error')^2 su `error', meanonly } display in green _n "Mean squared error: " in yellow `r(mean)' end This code was first presented in a pre-publication draft to Buckley (2003). There is the mlbeta_ll.ado file which calculates the log-likelihood, but isn't relevant to this post. To download -mlbeta-, type: . net from http://www2.bc.edu/~bucklesj There is, however, something which is not officially part of -mlbeta-: the addition of the -nocons- option. I wanted the routine to be able to include my choice of constants in the model, typically mutually-exclusive dummy variables, in much the same way as is handled by -reg-. I was advised by -mlbeta-'s author to try adding -nocons- to the code to get what I wanted, as, unlike -hascons-, this should work with -ml-'s estimating routines. As you can see from the code, it was added in exactly the same way as the -robust- option, which _is_ part of -mlbeta-. Unfortunately, -mlbeta- completely ignores -nocons-: . mlbeta sqgovote conadmin labadmin sqgpchg sqbeldm weakgovt, robust nocons note: labadmin dropped due to collinearity initial: log pseudolikelihood = 58.897248 [...] Iteration 5: log pseudolikelihood = 218.1697 Number of obs = 118 Wald chi2(4) = 59.30 Log pseudolikelihood = 218.1697 Prob > chi2 = 0.0000 ---------------------------------------------------------------------------- | Robust sqgovote | Coef. Std. Err. z P>|z| [95% Conf. Interval] -----------+---------------------------------------------------------------- eq1 | conadmin | -.0765583 .112732 -0.68 0.497 -.2975089 .1443923 sqgpchg | .8231001 .136534 6.03 0.000 .5554984 1.090702 sqbeldm | -.9002064 .1771583 -5.08 0.000 -1.24743 -.5529826 weakgovt | .1150282 .1120976 1.03 0.305 -.1046791 .3347354 _cons | -2.49654 .2900482 -8.61 0.000 -3.065024 -1.928056 -----------+---------------------------------------------------------------- eq2 | _cons | 3.069133 .369329 8.31 0.000 2.345261 3.793004 ---------------------------------------------------------------------------- Mean squared error: .006385 Were -nocons- to work, both -conadmin- and -labadmin- (a pair of mutually-exclusive dummy variables) would be included, as it is when using -reg-: . reg sqgovote conadmin labadmin sqgpchg sqbeldm weakgovt, robust nocons Regression with robust standard errors Number of obs = 118 F( 5, 113) = 19.93 Prob > F = 0.0000 R-squared = 0.4408 Root MSE = .08152 ---------------------------------------------------------------------------- | Robust sqgovote | Coef. Std. Err. t P>|t| [95% Conf. Interval] -----------+---------------------------------------------------------------- conadmin | .0666841 .0267032 2.50 0.014 .0137803 .1195878 labadmin | .0744811 .0283499 2.63 0.010 .0183148 .1306475 sqgpchg | .0548743 .0155478 3.53 0.001 .0240714 .0856773 sqbeldm | -.0588733 .0154754 -3.80 0.000 -.0895328 -.0282139 weakgovt | .0164249 .0159273 1.03 0.305 -.0151299 .0479797 ---------------------------------------------------------------------------- If anybody out there can shed some light as to what I'm missing, I'd be very grateful to you. CLIVE NICHOLAS |t: 0(044)7903 397793 Politics |e: [email protected] Newcastle University |http://www.ncl.ac.uk/geps References: Buckley J (2003) "Estimation of Models With Beta-Distributed Dependent Variables: A Replication and Extension to Paolino's Study" POLITICAL ANALYSIS 11(2): 204-5. Paolino P (2001) "Maximum Likelihood Estimation of Models With Beta-Distriuted Dependent Variables" POLITICAL ANALYSIS 9(4): 325-46. * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Adding -nocons- to -mlbeta-***From:*Richard Williams <[email protected]>

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