Thanks for the reply, that was a typo only in the post. as i was trying to
remove some 'sensitive names'.  In my real work,  i made sure that

1) this command runs without problem
qdata.glm = glm(X258 ~ ., family = binomial, data = qdata[
sample(dim(qdata)[1], 1000), ] )



2) these two gave a warning
qdata.sample = qdata[sample(dim(qdata)[1], 1000), ]
qdata.glm = glm(X258 ~ ., family = binomial, qdata.sample)

Warning message:
In glm.fit(x = X, y = Y, weights = weights, start = start, etastart =
etastart,  :
 fitted probabilities numerically 0 or 1 occurred


Can you explain why this is?

Thanks!




On Sat, Feb 14, 2009 at 8:09 AM, Duncan Murdoch <murdoch@stats.uwo.ca>wrote:

> On 13/02/2009 11:59 PM, Roger wrote:
>
>> Hello,
>>
>> I have a weird problem here.  What I want to do is that I need to draw
>> 1000
>> samples from a matrix, and use glm on them.
>>
>> when I used this command, it runs without the problem
>>
>>> qdata.glm = glm(X258 ~ ., family = binomial, data =
>>>
>> q2data[sample(dim(q2data)[1], 1000), ])
>>
>>
>> but if I drew the sample first and run glm() on that sample, it gave a
>> warning.
>>
>>> qdata.sample = q2data[sample(dim(qdata)[1], 1000), ]
>>>
>>
> This looks like a typo:  you took the dim of the wrong thing here.
>
> Duncan Murdoch
>
>  qdata.glm = glm(X258 ~ ., family = binomial, qdata.sample)
>>>
>> Warning message:
>> In glm.fit(x = X, y = Y, weights = weights, start = start, etastart =
>> etastart,  :
>>  fitted probabilities numerically 0 or 1 occurred
>>
>> Because I need to use that same sample later, I have to save it in
>> qdata.sample. therefore the first command does not work in my case because
>> I
>> cannot actually get the same 1000 sample after that.
>>
>> anyone knows how to solve this?
>>
>> Thanks!
>>
>>        [[alternative HTML version deleted]]
>>
>> ______________________________________________
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>> 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.
>>
>
>

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