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> From: peter dalgaard [pda...@gmail.com]
> Sent: Friday, February 06, 2015 7:35 PM
> To: Michael Dewey
> Cc: Mohamed Farah; r-help@r-project.org
> Subject: Re: [R] Interpreting a Logit regression result
>
> On 06 Feb 2015, at 16:58 , Michael Dewey wro
= 0.035087863 + 87.68931008 x.
Mohamed
From: Michael Dewey [i...@aghmed.fsnet.co.uk]
Sent: Friday, February 06, 2015 6:58 PM
To: Mohamed Farah; r-help@r-project.org
Subject: Re: [R] Interpreting a Logit regression result
Dear Mohamed
Your dataset did not
368
From: peter dalgaard [pda...@gmail.com]
Sent: Friday, February 06, 2015 7:35 PM
To: Michael Dewey
Cc: Mohamed Farah; r-help@r-project.org
Subject: Re: [R] Interpreting a Logit regression result
On 06 Feb 2015, at 16:58 , Michael Dewey wrote:
> Dear Mohamed
>
> Your dataset di
On 06 Feb 2015, at 16:58 , Michael Dewey 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 scie
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 t
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(d
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