On Mon, Dec 8, 2008 at 1:40 PM, David Duffy <David.Duffy@qimr.edu.au> wrote:

> On Sun, 7 Dec 2008, zhijie zhang wrote:
>
>  Dear Rusers,
>>  Sorry for re-post my question in this list. Some person has recommend
>> that this list is more specific for me.
>>  I have used R,S-PLUS and SAS to analyze the sample data "bacteria" in
>> MASS package. Their results are listed below.
>>
>> Q3:In SAS and other softwares, we can get p-values for the random effect
>> 'sigma', but i donot see the p-values in the results of R/SPLUS. I have
>> used
>> attributes() to look for them, but no p values. Anybody knows how to get
>> p-values for the random effect 'sigma',.
>>
>>
> Someone answered your specific questions before.
> Because this is a simple random intercept model, you can also use the
> glmmML R package, which gives:


Actually i will also fit  the random coefficient model. Here, i only use
this simple example to explain my questions. glmmML can only fit the random
intercept model.


>
> glmmML(y ~ trt + I(week > 2), cluster=ID, family=binomial, data=bacteria)
>
>                   coef se(coef)      z Pr(>|z|)
> (Intercept)      3.5482   0.6933  5.118 3.09e-07
> trtdrug         -1.3667   0.6768 -2.020 4.34e-02
> trtdrug+        -0.7826   0.6830 -1.146 2.52e-01
> I(week > 2)TRUE -1.5986   0.4754 -3.363 7.71e-04
>
> Standard deviation in mixing distribution:  1.242
> Std. Error:                                 0.4024
>
> Residual deviance: 192.3 on 215 degrees of freedom      AIC: 202.3
>
> You can then construct a test for the random effect.


Do u mean the following method?
 > model0<-glmmML(y ~ trt + I(week > 2), cluster=ID, family=binomial,
data=bacteria)
Warning message:
In model.response(mf, "numeric") :
  using type="numeric" with a factor response will be ignored
> model1<-glm(y ~ trt + I(week > 2), family=binomial, data=bacteria)
> anova(model0,model1)
 Error message occurred.
 Thanks.


>
>
> --
> | David Duffy (MBBS PhD)                                         ,-_|\
> | email: davidD@qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
> | Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
> | 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v
>



-- 
With Kind Regards,

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[***********************************************************************]
ZhiJie Zhang ,PhD
Dept.of Epidemiology, School of Public Health,Fudan University
Office:Room 443, Building 8
Office Tel./Fax.:+86-21-54237410
Address:No. 138 Yi Xue Yuan Road,Shanghai,China
Postcode:200032
Email:epistat@gmail.com <Email%3Aepistat@gmail.com>
Website: www.statABC.com
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