Or, as said, use -glm-.
Nick
[email protected]
[email protected]
>
> The -logistic- command was based on a program called
> -logiodds-that was made available to Stata users in the
> January 1991 "The Stata News". It was a stimulus to the
> creation of the Stata Technical Bulletin, which began in May
> of 1991. In fact, the first issue had a revised edition of
> -logiodds-. It was written to implement Hosmer-Lemeshow
> recomendations regarding covariate patterns and various GOF
> statistics, which were detailed in their then fairly new
> text. It was meant to be an alternative to Stata's -logit-
> command, which kept the observation based residuals.
>
> The current post -logistic- commands, lfit, lstat, and lroc,
> were provided as options to the -logiodds- command (I believe
> that the 2nd version, the one preceding Stata's official
> -logistic- command, was called -logiodd2- in STB-1).
>
> As it is now, -logistic- still retains the
> residuals-by-covariate-pattern approach to diagnostics. This
> underlays the fit statistics as well. Most other commercial
> software does not do this - hence possible differences in
> output. In my opinion, the Hosmer-Lemeshow approach of having
> fit statistics based on covariate pattern is preferable to
> simply using unadjusted individual observations as the basis
> of residual and fit statistics.
>
> The way to get what you want -- observation and not covariate
> patterns -- is to use -logit-, obtain the linear predictor
> and fit (mu) statistics using -predict-, and calculate the
> residuals and fit statistics using the appropriate formulae.
> You can find them in the manual, or in Hardin & Hilbe
> (2001-Stata Press). Calculating the residuals is really quiet easy.
>
>
> > At 06:55 PM 4/9/2004 +0100, Nick Cox wrote:
> > >To give this pot another stir, and to use
> > >mutually accessible data, -logit- and -glm-
> > >with logit link and binomial family give quite
> > >different deviance residuals.
> > >
> > >The pattern of -glm-'s makes sense,
> > >but that of -logit-'s is more puzzling.
> >
> > Ok, after looking in several wrong places, I finally found
> an explanation
> > in the Stata Reference Manual G-M, pp. 315-316. It says
> that "All the
> > residual and diagnostic statistics calculated by Stata
> [NOTE: 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.
> >
> > 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.
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