[R] get the wald chi square in binary logistic regression

[Renaud Lancelot]

severine.erhel at free.fr a écrit :
> hello,
> 
> I work since a few time on R and i wanted to know how to obtain the Wald chi
> square value when you make a binary logistic regression. In fact, i have the z
> value and the signification but is there a script to see what is the value of
> Wald chi square. You can see my model below,
> Best regards,
> 
> Séverine Erhel
> 
If you want a global test for several coeff associated with the same 
variable (e.g., form or criter2 in your example), you can fit the model 
without the variable and compare the 2 models with a likelihood ratio 
test (function anova): it is safer than the Wald test.

If you really want the Wald test, it is available in different packages: 
see for example the function wald.test in package aod.

Best,

Renaud


> 
> 
> 
> 
> [Previously saved workspace restored]
> 
> 
> 
>>m3 = glm(reponse2 ~ form + factor(critere2) ,family=binomial,data=mes.donnees)
>> summary (m3)
> 
> 
> Call:
> glm(formula = reponse2 ~ form + factor(critere2), family = binomial,
>     data = mes.donnees)
> 
> Deviance Residuals:
>     Min       1Q   Median       3Q      Max
> -2.5402   0.2064   0.3354   0.4833   1.4177
> 
> Coefficients:
>                          Estimate Std. Error z value Pr(>|z|)
> (Intercept)                0.5482     0.3930   1.395   0.1631
> form   Illustration        3.2904     0.6478   5.080 3.78e-07 ***
> form  Texte+illustration   2.6375     0.4746   5.557 2.74e-08 ***
> factor(critere2)2         -1.0973     0.5103  -2.150   0.0315 *
> factor(critere2)3         -0.9891     0.5107  -1.937   0.0528 .
> ---
> Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
> 
> (Dispersion parameter for binomial family taken to be 1)
> 
>     Null deviance: 227.76  on 218  degrees of freedom
> Residual deviance: 162.11  on 214  degrees of freedom
> AIC: 172.11
> 
> Number of Fisher Scoring iterations: 5
> 
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-- 
Dr Renaud Lancelot, vétérinaire
Projet FSP régional épidémiologie vétérinaire
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