If you did as the posting guide asked and not send HTML your message
might actually be readable. But I see no sign of the 'commented,
minimal, self-contained, reproducible' example.
The issue is most likely the starting values. See ?polr for how to
specify others (and it sounds like you can
Hi all, I'm trying to estimate an ordered probit model using polr: polr(Rating
~ Currac + Debt + Inflation + GDPpc + GDPgr + Ratio + Levelofdev + Eurozone +
Default, method ="probit") where Rating is an ordered discrete dependent
variable and the independent variables are a set of economic deter
> Feladó: Prof Brian Ripley [rip...@stats.ox.ac.uk]
> Küldve: 2013. július 4. 14:14
> To: Dániel Kehl
> Cc: r-help
> Tárgy: Re: [R] polr?
>
> On 04/07/2013 12:59, Dániel Kehl wrote:
>> Dear R users,
>>
>> I have a dataset with two ordered
Dear Prof Ripley,
could you be just a little more specific?
Thanks a lot
daniel
Feladó: Prof Brian Ripley [rip...@stats.ox.ac.uk]
Küldve: 2013. július 4. 14:14
To: Dániel Kehl
Cc: r-help
Tárgy: Re: [R] polr?
On 04/07/2013 12:59, Dániel Kehl wrote:
> D
On 04/07/2013 12:59, Dániel Kehl wrote:
Dear R users,
I have a dataset with two ordered variables, tr_x1 and tr_y1. A crosstable of
them can bee seen below.
tr_x1
tr_y1 -101
-1 629 100 629
0 1396 4353 1443
1 668 126 655
It is clear that if tr_x1 is 0, it ha
Dear R users,
I have a dataset with two ordered variables, tr_x1 and tr_y1. A crosstable of
them can bee seen below.
tr_x1
tr_y1 -101
-1 629 100 629
0 1396 4353 1443
1 668 126 655
It is clear that if tr_x1 is 0, it has an effect on tr_y1. A chi-square
statistic
On 11/01/2013 01:59, Alphan Kirayoglu wrote:
Hi,
Is there a function to calculate probabilities for new out-of-sample data
once we fit a model using the in-sample data?
predict(model, newdata=... ) seems to require the new data to be the same
size as the original data used to fit the model.
I
Hi,
Is there a function to calculate probabilities for new out-of-sample data
once we fit a model using the in-sample data?
predict(model, newdata=... ) seems to require the new data to be the same
size as the original data used to fit the model.
In short, I would like to fit a model and then pa
Dear List,
I have developed a model and am looking to predict a response for 1-6 ( it is
ordered i.e the difference between level 1 and 2 is the same as between level 2
and 3 etc.
I have used the predict function for a polr model (below) and a lrm model, and
both give similar results, however
Dear List,
I have developed a model and am looking to predict a response for 1-6 ( it is
ordered i.e the difference between level 1 and 2 is the same as between level 2
and 3 etc.
I have used the predict function for a polr model (below) and a lrm model, and
both give similar results, however
Dear All,
I am trying to use the packadge polr () to analyse ordinal categorical data
responses. Instead of using polr() directly, I have altered the script slightly
(imposed a constraint to make all the parameters greater than or equal to zero)
(see below),
fit <- list(coefficients = exp(be
Dea all,
Let's suppose I am studying a questionnaire survey and one of the
questions has three ordered categorical responses (say, A, B and C).
Eg
result<-ordered(c(rep("A",12),rep("B",37),rep("C",6)))
Assume the respondents are not grouped. The differences between the
subsequent levels can be,
Michael Friendly wrote:
For the following model,
library(vcd)
arth.polr <- polr(Improved ~ Sex + Treatment + Age, data=Arthritis)
summary(arth.polr)
where Improved is an ordered, 3-level response I'm looking for a
*simple* way to test
the validity of the proportional odds assumption, typically
For the following model,
library(vcd)
arth.polr <- polr(Improved ~ Sex + Treatment + Age, data=Arthritis)
summary(arth.polr)
where Improved is an ordered, 3-level response I'm looking for a
*simple* way to test
the validity of the proportional odds assumption, typically done via a
score test
On Sat, 10 Nov 2007, Anders Schwartz Corr wrote:
> I'm getting an error message using polr():
>
> Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) :
> initial value in 'vmmin' is not finite
>
> The outcome variable is ordinal and factored, and the independant variabl
Hi,
I'm getting an error message using polr():
Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) :
initial value in 'vmmin' is not finite
The outcome variable is ordinal and factored, and the independant variable
is continuous. I've checked the source code for bo
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