[R] calculating logit parameters (odd ratio is exactly one or zero)

[David Winsemius]

On Dec 12, 2011, at 3:51 PM, Uwe Ligges wrote:

> 1. The formula you used is not for a logistic but an ordinal  
> regression (since you are using the default gaussian family rather  
> than family="binomial" or whatever.

this this then produce one version of the "Armitage linear test of  
trend"?

>
> 2. R (nor any other software) can deal with perfect separation (nor  
> quasi-separation) of classes, since the problem is not well defined  
> in such a case as you found out already. R will give a warning in  
> that case, that the Fisher Scoring does not converge.
>
> LDA will give perfect results in such a case (well, unless the  
> within class covariance matrix is singular).
>
> Best,
> Uwe Ligges
>
>
>
> On 12.12.2011 11:46, wim nursal wrote:
>> Dear statistician experts,
>>
>> Sorry if this is a trivial question, or the old same question (i  
>> don't know
>> what is the efficient key word for this issue).
>> In order to understand the calculation of parameter of logistic  
>> regression,
>>  I did an exercise through spreadsheet following the procedural  
>> example
>> from a literature, or the available spreadsheet (with calculation  
>> formula).
>> I ended up with infinity (divided by zero) when the odd ratio is  
>> exactly 1
>> (FD=12) or invalid number when odd ratio is zero (MFD = 0) after log.
>> I am wondering  how R through GLM function (particularly logit or  
>> logistic
>> regression) treats the odds ratios or log odd ratios that is  
>> exatcly one or
>> zeros.
>>
>> The sample data is like this:
>> #HH Fsize FD
>> 1 1.29472 0
>> 2 1.6184 0
>> 3 2.4276 1
>> 4 2.4276 2
>> 5 20.23 2
>> 6 1.6184 3
>> 7 1.820 3
>> 8 0.4046 3
>> 9 6.069 4
>> 10 2.6299 4
>> 11 0.72828 5
>> 12 2.4276 5
>> 13 6.069 7
>> 14 4.8552 7
>> 15 2.32645 7
>> 16 1.6184 8
>> 17 1.0115 8
>> 18 1.0115 8
>> 19 5.2598 9
>> 20 2.023 10
>> 21 0.6069 10
>> 22 1.2138 11
>> 23 0.8092 11
>> 24 1.4161 11
>> 25 0.6069 11
>> 26 3.440 11
>> 27 1.2138 12
>> 28 1.2138 12
>> 29 0.4046 12
>> 30 1.2138 12
>>
>> Fsize is the farm size (acre or hectare).  Food deficit (FD) is the  
>> number
>> of months (last year from the survey took place) that an household  
>> had
>> bought food-grains (minimum = 0 month, maximum = 12 months or whole  
>> year
>> deficit).
>> Even though I "jitter"-ed the minimum or maximum FD value only (eg.
>> FD=0+1e-6 or FD=12-1e-6), nothing changed to the result.
>>
>> The formula I used is like this:
>> --------------------------------------------------------------
>> glm(FD ~ Fsize, data = subFS)
>> --
>> Coefficients:
>> (Intercept)        Fsize
>>      7.7913      -0.3092
>>
>> Degrees of Freedom: 29 Total (i.e. Null);  28 Residual
>> Null Deviance:      463
>> Residual Deviance: 425.5        AIC: 170.7
>> --------------------------------------------------------------
>>
>> I appreciate for any clarification.
>>
>> Best wishes,
>> Wim
>>
>>

David Winsemius, MD
Heritage Laboratories
West Hartford, CT