Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Richard Williams <richardwilliams.ndu@gmail.com> |

To |
statalist@hsphsun2.harvard.edu, "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: ordered logistic integration problems |

Date |
Thu, 21 Mar 2013 12:58:38 -0500 |

At 09:28 AM 3/21/2013, Bontempo, Daniel E wrote:

Thanks Richard. I follow about the difficulty of thresholds betweensparse categories, or even when some categories are not at alllevels of the IV's.I do lack insight into why "ologit" quickly picked thresholds andgave results, while gllamm and gologit2 seemed unable to pickthresholds. I am going to avoid thresholds and use the glm withlink(logit) family(binomial) as suggested in another reply, but itwould be great to have more insight into why ologit had no apparentproblem and gologit2 failed - even when I used the parallelassumption, and they were both estimating the same model.

ologit y x1 x2 x3 gologit2 y x1 x2 x3, pl

-----Original Message-----From: owner-statalist@hsphsun2.harvard.edu[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Stas KolenikovSent: Wednesday, March 20, 2013 8:26 PM To: statalist@hsphsun2.harvard.edu Subject: Re: st: ordered logistic integration problemsI second Richard. The message probably comes from the difficulty ofidentifying the threshold parameters for the categories with thefewest observations, especially if they interact in some odd wayswith the random effects and/or variance parameters. For as much as you(understandably) hate to run this as a linear model, this may be abetter option, as the prior work did. Or, at the other extreme,create a dummy "less than 100%", which will only have 10% non-trivial values.-- Stas Kolenikov, PhD, PStat (SSC) -- Senior Survey Statistician, Abt SRBI-- Opinions stated in this email are mine only, and do not reflectthe position of my employer-- http://stas.kolenikov.nameOn Wed, Mar 20, 2013 at 6:20 PM, Richard Williams<richardwilliams.ndu@gmail.com> wrote:> Occasionally adding the -difficult- option will work miracles. > > My guess, that you are spreading the data too thin. If I follow you, > the DV has 12 values, and 90% of the cases are a 1, which means the > other 11 values average less than 1% of the cases. With gologit2 you > are estimating 11 sets of coefficients. I am not surprised you have to > collapse to only 3 categories. > > But why are you using an ordinal model in the first place? Why not a > model specifically designed for proportions? See, for example, > > http://www.stata.com/support/faqs/statistics/logit-transformation/ > > http://www.ats.ucla.edu/stat/stata/faq/proportion.htm > > > At 06:04 PM 3/20/2013, Bontempo, Daniel E wrote: >> >> Can anyone explain the kind of data conditions that cause gllamm or >> glogit2 to spit out: >> >> flat or discontinuous region encountered numerical derivatives are >> approximate nearby values are missing could not calculate numerical >> derivatives missing values encountered r(430); >> >> >> I have a colleague with proportion data that only has about 12>> discrete values between 0 and 1 with about 90% 1's. Skew -3.27,Kurtosis>15.>> >> We want to model for 3 groups (between) and 3 occasions (within). >> Prior work published in 2000, had similar proportions and used HML >> (Gaussian) and got interpretable results. After looking at the >> distributions, I suggested ologit might be more appropriate than regress. >> >> I was already concerned about these proportion DVs because my >> colleague has calculated proportion correct of however many scorable >> events there were, and the number of events differs a lot from >> subject to subject. Some have 2 some have 10. BUT - my question for >> the moment is technical difficulty with numerical derivatives. >> >> Since there is occasion nested within person, I was interested in >> gllamm with the ologit link, as well as robust ologit with >> "cluster(subject)". I also tried glogit2 because I was unsure the >> parallel regression assumption was met. >> >> I easily get ologit to run. However both gllamm and glogit2 make >> similar complaints about missing or discontinuous numerical >> derivatives and do not complete. I tried the log-log link in glogit2>> since the values rise slowly from 0 and suddenly go to 1. I keptrounding to get fewer levels.>> >> I have to collapse to only 3 levels to get glogit2 to run. gllamm >> keeps telling me to use trace and check initial model, but when I do >> I see reasonable fixed effect values. >> >> Is ologit able to use an estimation method that avoids these >> integration issues? >> >> I am trying to get the disaggregated data so multilevel logistic >> regressions can be done, but it is not clear disaggregated data will >> be available. >> >> Any pointers, advice, suggestions, references ... all appreciated. >> >> >> * >> * 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/ > > > ------------------------------------------- > Richard Williams, Notre Dame Dept of Sociology > OFFICE: (574)631-6668, (574)631-6463 > HOME: (574)289-5227 > EMAIL: Richard.A.Williams.5@ND.Edu > WWW: http://www.nd.edu/~rwilliam > > > * > * 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/ * * 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/ * * 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/

------------------------------------------- Richard Williams, Notre Dame Dept of Sociology OFFICE: (574)631-6668, (574)631-6463 HOME: (574)289-5227 EMAIL: Richard.A.Williams.5@ND.Edu WWW: http://www.nd.edu/~rwilliam * * 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 integration problems***From:*"Bontempo, Daniel E" <deb193@ku.edu>

**References**:**st: ordered logistic integration problems***From:*"Bontempo, Daniel E" <deb193@ku.edu>

**Re: st: ordered logistic integration problems***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: st: ordered logistic integration problems***From:*Stas Kolenikov <skolenik@gmail.com>

**RE: st: ordered logistic integration problems***From:*"Bontempo, Daniel E" <deb193@ku.edu>

- Prev by Date:
**RE: st: While/if for individual observations** - Next by Date:
**Re: st: -ivregress- bug or feature?** - Previous by thread:
**RE: st: ordered logistic integration problems** - Next by thread:
**RE: st: ordered logistic integration problems** - Index(es):