Timeline for Is the percent of total deviance explained a useful model summary? [duplicate]
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| Jun 14, 2019 at 23:14 | comment | added | Tom Wenseleers | Without having to fit your model plus an intercept only model & a fully saturated model you can also calculated the R2 from the last iteration of the IRLS algo, which is just a weighted least squares regression - see stats.stackexchange.com/questions/412580/… | |
| Jun 14, 2019 at 23:12 | comment | added | Tom Wenseleers | The general deviance based R2, 1-residual deviance/null deviance, applies to any GLM with any family & link function. McFadden's was originally defined for logistic regression (where the log-likelihood of a saturated model=0) and in that case the above formula is correct, but the generically correct version would be 1-residual deviance/null deviance, see stats.stackexchange.com/questions/359906/… | |
| Feb 7, 2013 at 14:47 | history | closed | user88 | exact duplicate | |
| Feb 2, 2013 at 12:06 | comment | added | Corvus | Could you re-post your comment as an answer to your own question if it covers everything you wanted? Then you can accept your answer, and this won't appear as an unanswered question. | |
| Jan 6, 2012 at 17:01 | history | edited | Brett | CC BY-SA 3.0 |
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| Jan 6, 2012 at 16:58 | comment | added | Brett | Walking down another path, I stumbled onto a very clear answer to my question in by @probabilityislogic in the thread at: stats.stackexchange.com/questions/3559/… | |
| Jan 6, 2012 at 15:21 | history | edited | Brett | CC BY-SA 3.0 |
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| Jan 4, 2012 at 20:47 | comment | added | Brett | Indeed. The deviance R^2 from my question is the same as McFadden's measure. My question is really about interpretation of the deviance R^2 for non-Gaussian models. With a normal link it corresponds to SSR/SST and thus has a clean and neat interpretation. Is this true of other families? Do the results depend on the link used and the characteristics of the response? | |
| Jan 4, 2012 at 20:04 | comment | added | gung - Reinstate Monica | Is this: ats.ucla.edu/stat/mult_pkg/faq/general/psuedo_rsquareds.htm helpful, or do you mean something else? | |
| Jan 4, 2012 at 17:26 | history | tweeted | twitter.com/#!/StackStats/status/154614723453796352 | ||
| Jan 4, 2012 at 16:40 | history | edited | Brett | CC BY-SA 3.0 |
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| Jan 4, 2012 at 16:25 | history | asked | Brett | CC BY-SA 3.0 |