---------- Forwarded message ----------
From: Lao Meng <laomeng.3@gmail.com>
Date: 2011/1/19
Subject: Re: [R] question about result of loglinear analysis
To: David Winsemius <dwinsemius@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 <dwinsemius@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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