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From |
"Anat (Manes) Tchetchik" <anatmanes@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: ordered logistic regression with endogenous variable |

Date |
Thu, 11 Oct 2012 22:36:40 +0200 |

Okay! I'll try this path as well, Thanks much! On Thu, Oct 11, 2012 at 10:33 PM, Austin Nichols <austinnichols@gmail.com> wrote: > Anat (Manes) Tchetchik <anatmanes@gmail.com>: > You can also recast your ordinal variable as ranging from 0 to 1 > with outcomes in {0,.25,.5,.75,1} and use a fractional model > as described in e.g. > "Inference for partial effects in nonlinear panel-data models using Stata" > by Jeffrey Wooldridge, linked from > http://www.stata.com/meeting/snasug08/abstracts.html > > On Thu, Oct 11, 2012 at 2:04 PM, Anat (Manes) Tchetchik > <anatmanes@gmail.com> wrote: >> Thanks Jay, >> Actually this is not our main model (rather it is an "auxiliary" one >> aiming to validate some relations) our main model is a count one with >> IVs. >> I'm not sure I understood what did you mean by: problems with the >> residuals, I ran the IVregress and received the following stats. >> (with some of the coefficients signif. as expected ) >> Instrumental variables (2SLS) regression Number of obs = 603 >> Wald chi2(14) = 169.62 >> Prob > chi2 = 0.0000 >> R-squared = 0.3208 >> Root MSE = 1.0537 >> Anat >> >> >> On Thu, Oct 11, 2012 at 7:10 PM, JVerkuilen (Gmail) >> <jvverkuilen@gmail.com> wrote: >>> On Thu, Oct 11, 2012 at 12:38 PM, Anat (Manes) Tchetchik >>> <anatmanes@gmail.com> wrote: >>>> Hi Jay, It is a 5 categories var. however not symmetric (i.e. value 1 >>>> appears 10%, 2 appears 11%, 3- 22% , 4-27% and 5- 31%) so it doesn't >>>> fit into the IV estimator, shell I run gmm? >>> >>> That's not too bad in terms of skew, but you could have important >>> subgroups be skewed, so if for instance males are really positive on >>> the measure and females are really negative, the overall measure might >>> appear symmetric but not be at the level you want to analyze. >>> >>> You will get some attenuation of statistical power due to the coarse >>> response scale. You can try running an ordinary estimator, but if you >>> notice problems with the residuals, I'd switch to -gllamm- for an >>> ordinal probit model, or -gmm-. Specifying the model for either is not >>> a trivial matter, though, so I totally understand the desire to work >>> with a linear estimator! > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ -- Anat Tchetchik, PhD Department of Hotel and Tourism Management Guilford Glazer Faculty of Business and Management Ben-Gurion University of the Negev P.O.Box: 653 Beer-Sheva, Israel, 84105 E-mail: anat@som.bgu.ac.il Phone 972-(0)8-6479735 Fax: 972-(0)8-6472920 Web: http://cmsprod.bgu.ac.il/Eng/som/hotelmanage/Staff/Academic/ChechikA.htm * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: ordered logistic regression with endogenous variable***From:*"Anat (Manes) Tchetchik" <anatmanes@gmail.com>

**Re: st: ordered logistic regression with endogenous variable***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: ordered logistic regression with endogenous variable***From:*"Anat (Manes) Tchetchik" <anatmanes@gmail.com>

**Re: st: ordered logistic regression with endogenous variable***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: ordered logistic regression with endogenous variable***From:*"Anat (Manes) Tchetchik" <anatmanes@gmail.com>

**Re: st: ordered logistic regression with endogenous variable***From:*Austin Nichols <austinnichols@gmail.com>

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