glm.fit: fitted probabilities numerically 0 or 1 occurred & glm.fit: algorithm did not converge

1. No, changing to factor will make no difference.

2. I think that most likely your problem is your model is not
estimable/your design matrix is singular.  You should resolve this by
consulting with a local statistical expert or, if your data set is not
too large or confidential, posting your full dataset using dput() (see
?dput for how to do this).

Cheers,
Bert
Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Fri, Aug 12, 2016 at 7:58 AM, Shivi Bhatia <shivipmp82 at gmail.com>
wrote:

Hi Michael,

There is no output as the model does not generate any coefficients and
simply throws this error.

I hope you are not asking for a reproducible example.

On Fri, Aug 12, 2016 at 7:30 PM, Michael Dewey <lists at dewey.myzen.co.uk>
wrote:

Dear Shivi

Can you show us the output?

And please do not post in HTML as it will mangle your post into
unreadability.

On 12/08/2016 10:10, Shivi Bhatia wrote:

Hi Team,

I am creating *my first* Logistic regression on R Studio. I am working

on

a

C-SAT data where rating (score) 0-8 is a dis-sat whereas 9-10 are SAT.

As

these were in numeric form so i had as below created 2 classes:

new$survey[new$score>=0 & new$score<=8]<- 0
new$survey[new$score>=9]<- 1
This works fine however the class still shows as "numeric" and levels
shows
as "NULL". Do i still need to use "as.factor" to let R know these are
categorical variables.

Also i have used the below code to run a logistic regression with all

the

possible predictor variables:
glm.fit= glm(survey ~ support_cat + region+ support_lvl+ skill_group+
application_area+ functional_area+
          repS+ case_age+ case_status+ severity_level+
          sla_status+ delivery_segmentation, data = SFDC, family =
binomial)

But it throws an error:-
Warning messages:
1: glm.fit: algorithm did not converge
2: glm.fit: fitted probabilities numerically 0 or 1 occurred

I checked online for the error and it says:
"glm() uses an iterative re-weighted least squares algorithm. The
algorithm
hit the maximum number of allowed iterations before signalling
convergence.
The default,
documented in ?glm.control is 25."

Kindly suggest on the above case and if i have to change my outcome

var as

as.factor.

Thank you, Shivi

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--
Michael
http://www.dewey.myzen.co.uk/home.html

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