[R] When models and anova(model) disagree...

[Frank Harrell]

Without seeing the model I'm not clear on the cause.  In general it is not
very useful to compute 1 d.f. tests for parameters that represent only part
of a meaningful hypothesis.

Note that anova.lrm computes Wald statistics, which are subject to the
Hauck-Donner effect (which may not be the cause of your problem).

Frank


bbolker wrote:
> 
> Greg Snow <Greg.Snow <at> imail.org> writes:
> 
>> The individual tests on coefficients in logistic regression 
>> are generally based on a Wald test statistic. 
>> Unfortunately there is a bit of a paradox possible in this
>>  case where the coefficient is highly
>> significant, but due to a flattening of the likelihood the 
>> standard error is overestimated and the
>> p-value ends up non-significant.  
>> The anova function uses the likelihood ratio test which is not affected
>> by this and is the more trustworthy statistic to use.
> 
>> I assume that you are using the lrm function from 
>> the rms package, the book that that package goes along with
> 
>   (Harrell, Regression Modeling Strategies)
> 
>> gives more detail (including the name of the paradox
>>  which I don't remember at the moment (and my copy of the
>> book is currently 40 miles away)).
> 
>   Hauck-Donner (also described in Venables & Ripley MASS)
> 
>   [Gmane
>      does
>        not like the fact that I have given
>            a short answer.]
> 
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-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
--
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