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From |
Austin Nichols <[email protected]> |

To |
[email protected] |

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

Date |
Thu, 11 Oct 2012 16:33:14 -0400 |

Anat (Manes) Tchetchik <[email protected]>: 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 <[email protected]> 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) > <[email protected]> wrote: >> On Thu, Oct 11, 2012 at 12:38 PM, Anat (Manes) Tchetchik >> <[email protected]> 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/

**Follow-Ups**:**Re: st: ordered logistic regression with endogenous variable***From:*"Anat (Manes) Tchetchik" <[email protected]>

**References**:**st: ordered logistic regression with endogenous variable***From:*"Anat (Manes) Tchetchik" <[email protected]>

**Re: st: ordered logistic regression with endogenous variable***From:*"JVerkuilen (Gmail)" <[email protected]>

**Re: st: ordered logistic regression with endogenous variable***From:*"Anat (Manes) Tchetchik" <[email protected]>

**Re: st: ordered logistic regression with endogenous variable***From:*"JVerkuilen (Gmail)" <[email protected]>

**Re: st: ordered logistic regression with endogenous variable***From:*"Anat (Manes) Tchetchik" <[email protected]>

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