22 Oct
2011
22 Oct
'11
12:29 p.m.
Hi,
I am getting the below warning messages from Zelig:
Warning messages:
1: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
2: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
3: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
4: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
5: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
Background: I am running a probit model where my dependent variable is a
proportion between 0 and 1 (it is a percentage of votes). I used Amelia to
overcome my missing data issues.
I'm not sure what the warnings mean. I just want to be certain that I am not
running an erroneous model.
Thank you for your time and help.
Sera
22 Oct
22 Oct
12:31 p.m.
Dear Sera,
I'm guessing you're using weights?
Yph
On Sat, Oct 22, 2011 at 9:29 AM, Sera Choma <sera.onalan(a)gmail.com> wrote:
Hi,
I am getting the below warning messages from Zelig:
Warning messages:
1: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
2: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
3: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
4: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
5: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
Background: I am running a probit model where my dependent variable is a
proportion between 0 and 1 (it is a percentage of votes). I used Amelia to
overcome my missing data issues.
I'm not sure what the warnings mean. I just want to be certain that I am
not running an erroneous model.
Thank you for your time and help.
Sera
12:34 p.m.
When you used Amelia to impute, are all of the values in your DV either 0 or
1?
The error message means that your model is returning undefined (due to too
much missing data).
On Sat, Oct 22, 2011 at 12:29 PM, Sera Choma <sera.onalan(a)gmail.com> wrote:
Hi,
I am getting the below warning messages from Zelig:
Warning messages:
1: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
2: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
3: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
4: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
5: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
Background: I am running a probit model where my dependent variable is a
proportion between 0 and 1 (it is a percentage of votes). I used Amelia to
overcome my missing data issues.
I'm not sure what the warnings mean. I just want to be certain that I am
not running an erroneous model.
Thank you for your time and help.
Sera
12:41 p.m.
All values for my DV are between 0 and 1, ie some are .25 etc. Also, some
are 0.
Should I remove some of the variables I'm imputing?
Sera
On Sat, Oct 22, 2011 at 12:34 PM, Olivia Lau <olivia.lau(a)post.harvard.edu>wrote;wrote:
When you used Amelia to impute, are all of the values
in your DV either 0
or 1?
The error message means that your model is returning undefined (due to too
much missing data).
On Sat, Oct 22, 2011 at 12:29 PM, Sera Choma <sera.onalan(a)gmail.com>wrote;wrote:
Hi,
I am getting the below warning messages from Zelig:
Warning messages:
1: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
2: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
3: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
4: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
5: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
Background: I am running a probit model where my dependent variable is a
proportion between 0 and 1 (it is a percentage of votes). I used Amelia to
overcome my missing data issues.
I'm not sure what the warnings mean. I just want to be certain that I am
not running an erroneous model.
Thank you for your time and help.
Sera
4593
days inactive
4593
days old
3 comments
3 participants
participants (3)
-
Olivia Lau -
Sera Choma -
Yph Lelkes