On 06 Feb 2015, at 16:58 , Michael Dewey <i...@aghmed.fsnet.co.uk> wrote:

> Dear Mohamed
> 
> Your dataset did not make it through, the list strips most attachments.
> 
> In my area of application I would be suspicious that such an odds ratio was 
> the result of a data error or my misunderstanding of the underlying science. 
> You are probably in the best position to judge both of these in your area.
> 

If both variables are binary, a table would be informative:

with(divs, table(Div, PRFD))

The output is roughly consistent with odds 1:30 if PRFD==0 and 3:1 if PRFD==1.  
That sounds extreme, but not entirely implausible, depending on field of 
application.


> Michael
> 
> 
> On 06/02/2015 07:42, Mohamed Farah wrote:
>> I have run a logit regression with two categorical variables (with 0 and 1)  
>> as the values. i.e. payment (1) / non-payment(0) on profit (profitable =1, 
>> non-profitable=0) on 375 entities. Here is the result from R:
>> 
>> 
>> 
>>> divgress <-glm(Div~PRFD, family=binomial(link="logit"), data=divs)
>>> summary(divgress)
>> 
>> Call:
>> glm(formula = Div ~ PRFD, family = binomial(link = "logit"),
>>     data = divs)
>> 
>> Deviance Residuals:
>>     Min       1Q   Median       3Q      Max
>> -1.6765  -0.2626   0.7502   0.7502   2.6017
>> 
>> Coefficients:
>>             Estimate Std. Error z value Pr(>|z|)
>> (Intercept)  -3.3499     0.7194  -4.656 3.22e-06 ***
>> PRFD          4.4738     0.7311   6.119 9.41e-10 ***
>> ---
>> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>> 
>> (Dispersion parameter for binomial family taken to be 1)
>> 
>>     Null deviance: 491.84  on 376  degrees of freedom
>> Residual deviance: 371.78  on 375  degrees of freedom
>> AIC: 375.78
>> 
>> Number of Fisher Scoring iterations: 6
>> 
>> 
>> 
>> My question is that the coefficient of the independent variable (log-odds) 
>> at 4.4738  is difficult to interpret. I have obtained the exponent of the 
>> coefficient below and as the result of 87.69..   shown below shows, the 
>> number is high which makes suspicious that there is something not working 
>> right.
>> 
>> 
>> 
>>> exp(coef(divgress))
>> (Intercept)        PRFD
>>  0.03508772 87.69230769
>>> 
>> 
>> 
>> 
>> The dataset is attached. I appreciate your help.
>> 
>> 
>> 
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> 
> -- 
> Michael
> http://www.dewey.myzen.co.uk
> 
> ______________________________________________
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-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk  Priv: pda...@gmail.com

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