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Lao Meng

2011-Jan-19 01:45 UTC

[R] question about result of loglinear analysis

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.

How does this happen?Why all the coeffients are 1 or very near to 1?

Thanks!

My best
-------------- next part --------------
area	nation	fre
1	1	0
1	2	0
1	3	85
1	4	2
1	5	0
1	6	0
1	7	0
1	8	0
1	9	1
1	10	0
1	11	0
2	1	0
2	2	0
2	3	253
2	4	2
2	5	0
2	6	10
2	7	0
2	8	0
2	9	1
2	10	2
2	11	0
3	1	5
3	2	0
3	3	1242
3	4	0
3	5	2
3	6	0
3	7	1
3	8	0
3	9	10
3	10	5
3	11	3
4	1	0
4	2	0
4	3	290
4	4	1
4	5	0
4	6	0
4	7	0
4	8	2
4	9	0
4	10	0
4	11	62
5	1	0
5	2	0
5	3	382
5	4	0
5	5	0
5	6	0
5	7	3
5	8	7
5	9	0
5	10	0
5	11	0
6	1	0
6	2	0
6	3	119
6	4	39
6	5	0
6	6	0
6	7	0
6	8	0
6	9	383
6	10	1
6	11	0
7	1	12
7	2	12
7	3	376
7	4	5
7	5	8
7	6	0
7	7	10
7	8	9
7	9	0
7	10	52
7	11	0

David Winsemius

2011-Jan-19 01:56 UTC

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[R] question about result of loglinear analysis

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 at 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
> and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
West Hartford, CT

Lao Meng

2011-Jan-19 05:22 UTC

head link

[R] Fwd: question about result of loglinear analysis

---------- 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
>
>
	[[alternative HTML version deleted]]

Dennis Murphy

2011-Jan-19 09:20 UTC

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[R] question about result of loglinear analysis

Hi:

Well, you fit a saturated model. How many degrees of freedom do you have
left for error? The fact that the standard errors are so huge relative to
the estimates is a clue.

Taking a look at your data, it's pretty clear that nation 3 is an
outstanding outlier on its own. It is clearly - nay, blatantly - different
from the other nations in the sample. Look at

boxplot(fre ~ nation, data = data_Analysis)
boxplot(sqrt(fre) ~ nation, data = data_Analysis)

the latter to deal with the huge outlier near 1200 in the original data.
Even on the square root scale, nation 3 sticks out like a sore thumb. 43/77
of your responses have zero frequency, so you should probably be looking
into zero-inflated Poisson models and some of its relatives. Here is one
citation to get you started:

http://www.jstatsoft.org/v27/i08/paper

Package VGAM also has functionality to fit these types of models.

Using package sos, I typed

# Install package sos first if you don't have it:
library(sos)
findFn('zero Poisson')

which found 255 matches; you should find several packages that pertain to
zero-inflated/zero-altered Poisson models.

In the absence of the scientific background behind the data, the dominance
of nation 3 may well mask more subtle effects among the other nations, so
you might want to consider analyses with and without nation 3.

HTH,
Dennis

On Tue, Jan 18, 2011 at 5:45 PM, Lao Meng <laomeng.3@gmail.com> 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.
>
> How does this happen?Why all the coeffients are 1 or very near to 1?
>
> Thanks!
>
> My best
>
> ______________________________________________
> 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
> and provide commented, minimal, self-contained, reproducible code.
>
>
	[[alternative HTML version deleted]]

R help - Jan 2011 - question about result of loglinear analysis

[R] question about result of loglinear analysis

[R] question about result of loglinear analysis

[R] Fwd: question about result of loglinear analysis

[R] question about result of loglinear analysis

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