| From | Constantine Daskalakis <[email protected]> |
| To | [email protected] |
| Subject | RE: st: Residuals in Logistic Regression |
| Date | Fri, 09 Apr 2004 15:28:28 -0400 |
At 03:07 PM 4/9/2004, Richard Williams wrote:
I think it really means Stata logistic regression and some related routines] are in terms of covariate patterns, not observations. That is, all observations with the same covariate patterns are given the same residual and diagnostic statistics." It says that Hosmer and Lemeshow argue that this is the better way to do it.Correct. That's what it is and that is how H&L define the deviance residuals (p.138).
They may be right, but even Stata isn't consistent across routines in the handling of this. I'd like for -predict- to offer residual stats that were based on the individual observations and not the covariate patterns.I never understood the rationale of this whole business. It has to do with whether you focus on individual observations (in which case your degrees of freedom equal your total sample size) or covariate patterns (in which case, the degrees of freedom are dependent on what covariates you include in the model). H&L prefer the latter. I think it leads to certain unintuitive situations. For example, suppose you fit a model with only an intercept. All the residuals will be 0 in this case (there's only a single covariate pattern, ie, the entire sample). Surely that cannot be right? Perfect fit? I don't think so.
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