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RE: st: Residuals in Logistic Regression
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
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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Constantine Daskalakis, ScD
Biostatistics Section, Thomas Jefferson University,
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