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From |
Marcello Pagano <pagano@hsph.harvard.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Binomial regression |

Date |
Fri, 03 Aug 2007 11:27:55 -0400 |

Convenience should not be the determining factor, rather which model best fits the data should be what governs our choices.

m.p.

Tim Wade wrote:

Thanks Constantine for sharing your results.

There are certainly cases where the risk difference is a more

appropriate or desirable measure. In these cases, the identity link

does have the significant advantage of being linear on the probability

scale instead of the log odds scale. And while we can convert log-odds

to probability, it is often convenient, especially when we have a

multivariate model to be able to interpret the regression coefficients

as the expected change in the probability (i.e, the risk difference)

holding other factors constant. Since probability is not linear in the

logistic model, similar inferences about probability or risk

differences cannot be made with the logistic model. If one wants to

make a statement about risk differences from multivariate logistic

model, it needs to be with regard to holding the other covariates at

some specific constant value, such as zero or at their mean values.

Tim

On 8/2/07, Marcello Pagano <pagano@hsph.harvard.edu> wrote:

Sorry to disagree with your first sentence, Constantine.*

Logistic regression stipulates a linear relationship of covariates with

the log of the odds of an event (not odds ratios).

From this it is straightforward to recover the probability (or risk, if

you prefer that label) of the event.

Don't understand your aversion to logistic regression to achieve what

you want to achieve.

If you don't like the shape of the logistic, then any other cdf will

provide you with a transformation to obey the constraints inherent in

modeling a probability. The uniform distribution that you wish to use

has to be curtailed, as others have pointed out.

m.p.

Constantine Daskalakis wrote:

No argument about logistic regression. But that gives you odds ratios.*

What if you want risk differences instead?

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**References**:**Re: st: Binomial regression***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Binomial regression***From:*Constantine Daskalakis <C_Daskalakis@mail.jci.tju.edu>

**Re: st: Binomial regression***From:*Marcello Pagano <pagano@hsph.harvard.edu>

**Re: st: Binomial regression***From:*"Tim Wade" <wadetj@gmail.com>

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