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

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

From |
Maarten Buis <maartenlbuis@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: Re: st: Comparison of Coefficients in Conditional Logistic regression |

Date |
Wed, 20 Jun 2012 15:12:48 +0200 |

On Wed, Jun 20, 2012 at 2:43 PM, A. Karvounidis wrote: > thanks for the help. Could you please be more specific with what do you mean by "derive good starting values > from the separately estimated models(*), and use those."? Moreover you said that if I want to use coefficients from the separetly regressions I need to do some computations. What computations can I do in order to compare them? thats the point... Just to be sure we are on the same page: you have to use the model with interaction effects. There is no other way. The challenge is to estimate it. Have you tried estimating your model with interactions after appropriately centering your variable? This is the first thing you must try, as all other "solutions" will require lots of work for you and there is not much we can do to help you. Assuming you tried to estimate the interaction model with appropriately centered variables and it failed to converge. Than the next step would be to seriously seriously seriously reconsider the model, as in all likelihood you are either making a mistake with the specification of the model or your model just too complex to be meaningfully estimated with your data. Only than can we start to think about starting values. In that case estimate the separate models. Than just write down the separate models and the model with interaction effects and derive the relationship between the two. I would start with sticking to the additive form of the model, i.e. the effects on the log odds of success. The math is typically simple, usually no more than some adding and subtracting, but there are many different ways in which you can parameterize both models, and the results will critically depend on that. So you need to do this yourself, as only you know how you parameterized your model. After that you use those results to derive the "values" for the interaction model from the separate models, store those initial values in a matrix, assign the appropriate column names to it and feed it to -clogit- using the -from()- option. -- Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * 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/

**References**:**Re: Re: st: Comparison of Coefficients in Conditional Logistic regression***From:*"A. Karvounidis" <A.Karvounidis@uvt.nl>

- Prev by Date:
**Re: st: weighted logistic regression in stata** - Next by Date:
**st: Error message when using estat teffects** - Previous by thread:
**Re: Re: st: Comparison of Coefficients in Conditional Logistic regression** - Next by thread:
**Re: st: Beta coefficients are not equal to coefficients on standardized variables?** - Index(es):