---------- Forwarded message ----------
From: Lao Meng <laomen...@gmail.com>
Date: 2011/1/19
Subject: Re: [R] question about result of loglinear analysis
To: David Winsemius <dwinsem...@comcast.net>
My command and result are :
> result_sat<-summary(glm_sat)
> result_coe<-result_sat$coefficients
> result_coe
Estimate Std. Error z value Pr(>|z|)
(Intercept) -26.3025850551 312167 -0.0000842581467488 1
area2 -0.0000000391 441470 -0.0000000000000887 1
area3 27.9120229675 312167 0.0000894138474346 1
area4 -0.0000000396 441470 -0.0000000000000897 1
area5 -0.0000000376 441470 -0.0000000000000852 1
area6 -0.0000000399 441470 -0.0000000000000903 1
area7 28.7874917049 312167 0.0000922183388256 1
nation2 -0.0000000349 441470 -0.0000000000000790 1
nation3 30.7452363116 312167 0.0000984898110791 1
nation4 26.9957322356 312167 0.0000864785861745 1
nation5 -0.0000000231 441470 -0.0000000000000523 1
nation6 -0.0000000349 441470 -0.0000000000000790 1
nation7 -0.0000000286 441470 -0.0000000000000647 1
nation8 -0.0000000367 441470 -0.0000000000000832 1
nation9 26.3025850551 312167 0.0000842581467484 1
nation10 -0.0000000492 441470 -0.0000000000001115 1
nation11 -0.0000000372 441470 -0.0000000000000842 1
area2:nation2 0.0000000364 624333 0.0000000000000584 1
area3:nation2 -27.9120229706 540689 -0.0000516231080772 1
area4:nation2 0.0000000366 624333 0.0000000000000587 1
area5:nation2 0.0000000332 624333 0.0000000000000531 1
area6:nation2 0.0000000368 624333 0.0000000000000590 1
area7:nation2 0.0000000349 441470 0.0000000000000790 1
area2:nation3 1.0907382714 441470 0.0000024706943226 1
area3:nation3 -25.2301959615 312167 -0.0000808228373513 1
area4:nation3 1.2272297061 441470 0.0000027798689650 1
area5:nation3 1.5027693897 441470 0.0000034040098332 1
area6:nation3 0.3364722765 441470 0.0000007621628078 1
area7:nation3 -27.3005538180 312167 -0.0000874550567977 1
area2:nation4 0.0000000391 441470 0.0000000000000887 1
area3:nation4 -54.9077552406 441470 -0.0001243747310970 1
area4:nation4 -0.6931471409 441470 -0.0000015700876663 1
area5:nation4 -26.9957322354 540689 -0.0000499284341769 1
area6:nation4 2.9704145054 441470 0.0000067284576415 1
area7:nation4 -27.8712009730 312167 -0.0000892830775653 1
area2:nation5 0.0000000218 624333 0.0000000000000349 1
area3:nation5 -0.9162907088 441470 -0.0000020755430662 1
area4:nation5 0.0000000248 624333 0.0000000000000397 1
area5:nation5 0.0000000228 624333 0.0000000000000365 1
area6:nation5 0.0000000250 624333 0.0000000000000401 1
area7:nation5 -0.4054650850 441470 -0.0000009184424089 1
area2:nation6 28.6051702221 540689 0.0000529050794386 1
area3:nation6 -27.9120229740 540689 -0.0000516231080491 1
area4:nation6 0.0000000368 624333 0.0000000000000589 1
area5:nation6 0.0000000347 624333 0.0000000000000556 1
area6:nation6 0.0000000370 624333 0.0000000000000593 1
area7:nation6 -28.7874917077 540689 -0.0000532422818772 1
area2:nation7 0.0000000300 624333 0.0000000000000481 1
area3:nation7 -1.6094378839 441470 -0.0000036456308179 1
area4:nation7 0.0000000302 624333 0.0000000000000484 1
area5:nation7 27.4011974099 540689 0.0000506783395313 1
area6:nation7 0.0000000304 624333 0.0000000000000488 1
area7:nation7 -0.1823215282 441470 -0.0000004129870365 1
area2:nation8 0.0000000413 624333 0.0000000000000662 1
area3:nation8 -27.9120229714 540689 -0.0000516231080553 1
area4:nation8 26.9957323120 540689 0.0000499284343439 1
area5:nation8 28.2484952785 540689 0.0000522454114350 1
area6:nation8 0.0000000387 624333 0.0000000000000620 1
area7:nation8 -0.2876820357 441470 -0.0000006516452129 1
area2:nation9 0.0000000391 441470 0.0000000000000887 1
area3:nation9 -25.6094378745 312167 -0.0000820377073224 1
area4:nation9 -26.3025850534 540689 -0.0000486464628969 1
area5:nation9 -26.3025850556 540689 -0.0000486464628975 1
area6:nation9 5.9480350291 441470 0.0000134732380515 1
area7:nation9 -55.0900767979 441470 -0.0001247877181979 1
area2:nation10 26.9957323240 540689 0.0000499284343203 1
area3:nation10 0.0000000492 441470 0.0000000000001115 1
area4:nation10 0.0000000497 624333 0.0000000000000796 1
area5:nation10 0.0000000506 624333 0.0000000000000810 1
area6:nation10 26.3025851442 540689 0.0000486464630491 1
area7:nation10 1.4663371180 441470 0.0000033214849874 1
area2:nation11 0.0000000385 624333 0.0000000000000616 1
area3:nation11 -0.5108255866 441470 -0.0000011571005711 1
area4:nation11 30.4297195169 540689 0.0000562795716938 1
area5:nation11 0.0000000357 624333 0.0000000000000572 1
area6:nation11 0.0000000391 624333 0.0000000000000626 1
area7:nation11 -28.7874917056 540689 -0.0000532422818467 1
2011/1/19 David Winsemius <dwinsem...@comcast.net>
> On Jan 18, 2011, at 8:45 PM, Lao Meng wrote:
>
> Hi all:
>> Here's a question about result of loglinear analysis.
>> There're 2 factors:area and nation.The raw data is in the attachment.
>>
>> I fit the saturated model of loglinear with the command:
>> glm_sat<-glm(fre~area*nation, family=poisson, data=data_Analysis)
>>
>> After that,I extract the coefficients:
>> result_sat<-summary(glm_sat)
>> result_coe<-result_sat$coefficients
>>
>> I find that all the coeffients are 1 or very near to 1.
>>
>
> I didn't get that result with that code. Did you perhaps attach some other
> data structure that you have failed to inform us about?
>
> > result_coe
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 5.40707901 0.06797962 79.53971 0.000000e+00
> area -0.12665730 0.01498742 -8.45091 2.890419e-17
> nation -0.42998381 0.01615198 -26.62112 3.867012e-156
> area:nation 0.04823113 0.00317437 15.19392 3.879947e-52
>
>
>
>
>> How does this happen?Why all the coeffients are 1 or very near to 1?
>>
>> Thanks!
>>
>> My best
>> <area_nation.txt>______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> David Winsemius, MD
> West Hartford, CT
>
>
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