Displaying 20 results from an estimated 20000 matches similar to: "Need advice about models with ordinal input variables"
2010 Sep 08
4
coxph and ordinal variables?
Dear R-help members,
Apologies - I am posting on behalf of a colleague, who is a little puzzled
as STATA and R seem to be yielding different survival estimates for the same
dataset when treating a variable as ordinal. Ordered() is used to represent
an ordinal variable) I understand that R's coxph (by default) uses the Efron
approximation, whereas STATA uses (by default) the Breslow. but we
2002 May 30
2
Systems of equations in glm?
I have a student that I'm encouraging to use R rather than SAS or Stata
and within just 2 weeks he has come up with a question that stumps me.
What does a person do about endogeneity in generalized linear models?
Suppose Y1 and Y2 are 5 category ordinal dependent variables. I see
that MASS has polr for estimation of models like that, as long as they
are independent. But what if the
2002 Oct 10
4
Correspondence analysis/optimal scaling with ordinal variable
Dear R specialists,
I have a multivariate statistics question that I want to submit to
the R community (which conveys a very good statistical knowledge).
I need to perform an optimal scaling based on a discrete variable and
an ordinal variable. The discrete variable, Area, defines a
geographical area. The ordinal variable, EducationLevel, describes
the education level of individuals (the
2006 May 22
1
Ordinal Independent Variables
When I run "lrm" from the Design package, I get a warning about
contrasts when I include an ordinal variable:
Warning message:
Variable ordfac is an ordered factor.
You should set
options(contrasts=c("contr.treatment","contr.treatment"))
or Design will not work properly. in: Design(eval(m, sys.parent()))
I don't get this message if I use glm with
2012 Mar 24
0
Help ordinal mixed model!
Good afternoon, gentlemen! After several days studying and researching on
categorical data (various forums with answers from the owner of the library
- all incipient) how to interpret the output the function MCMCglmm, come to
enlist the help of you, if someone has already worked with MCMCglmm function
in the case of variables ordinal dependent. I've read and reread all the
pdf's of the
2010 Oct 19
2
Clustering with ordinal data
Hello
I've been asked to help evaluate a vegetation data set, specifically to
examine it for community similarity. The initial problem I see is that the
data is ordinal. At best this only captures a relative ranking of
abundance and ordinal ranks are assigned after data collection. I've
been trying to find a procedure in R that can handle ordinal based
classification and so far have
2012 Mar 21
0
multivariate ordinal probit regression vglm()
Hello, all.
I'm investigating the rate at which skeletal joint surfaces pass
through a series of ordered stages (changes in morphology). Current
statistical methods in this type of research use various logit or
probit regression techniques (e.g., proportional odds logit/probit,
forward/backward continuation ratio, or restricted/unrestricted
cumulative probit). Data typically include the
2011 Mar 28
1
ordination in vegan
Hi all,
I have site data with plant species cover and am looking for trends. I'm
kind of new to this, but have done lots of reading and can't find an answer.
I tried decorana (I know it's been replaced by ca.) and see a trend, but I'm
not sure what it means. Is there a way to get the loadings/eigenvectors of
the axes (like in PCA)? Is there a way to do this with rda() too? How
2005 Sep 21
2
controlling usage of digits & scientific notation in R plots; postscript margins
Dear R users:
I assigned students to make some graphs and I'm having trouble answering
some questions that they have. We are all working on R 2.1 on Fedora
Core Linux 4 systems.
1. In the plot, the axis is not labeled by "numbers", but rather
scientific notation like "-2e+08" or such. We realize that means
-200,000,000. We want to beautify the plot. We would rather
2000 Aug 06
1
Trying to "pretty up" output from R job
Running R 1.1 on RedHat Linux 6.2.
I need to write a shell script that goes through a bunch of directories
of simulation output, creating summary files that have the mean and
standard deviation of the variables found in the data files in each
directory. I've got the R code doing almost the right thing. It reads
in data, then gets the mean and standard deviation for the numeric
variables,
2009 Oct 12
1
Ordinal response model
I have been asked to analyse some questionnaire data- which is not data I'm
that used to dealing with. I'm hoping that I can make use of the nabble
expertise (again).
The questionnaire has a section which contains a particular issue and then
questions which are related to this issue (and potentially to each other):
1) importance of the issue (7 ordinal categories from -3 to +3)
2) impact
2002 Mar 26
0
correlation matrix for mixed contin/nominal/ordinal variables
I have a consulting client with data containing a mixture of
continuous, nominal, and ordinal variables, who wishes
to do some correlational analyses.
Ignoring for the moment whether this is wise or useful,
is there some way to calculate a matrix using, for example,
polychoric correlations for pairs of nominal variables,
or correlations based on normal scores for ordinal variables?
[The PRELIS
2011 Apr 13
0
ordinal predictor in anova
Hi,
I have a dataset with a continuous response variable and, among
other predictors, an ordinal variable.
Here is what it could look like
treatment <- factor(rep(c("AA", "AC", "AD","AE", "AB"), each = 10))
length <- c(75, 67, 70, 75, 65, 71, 67, 67, 76, 68,
57, 58, 60, 59, 62, 60, 60, 57, 59, 61,
58,
2004 Oct 22
3
dotplot & lattice problems: y axis values and bg color output in jpg
I have a linux system with Fedora Core 2 and R-2.0.
I was comparing plots made with plot() and dotplot() and discovered a
problem. Although the dots are positioned correctly, the numerical
labels in the dotplot y axis are not correct.
I put copies here:
http://lark.cc.ku.edu/~pauljohn/R/plotTrouble1.jpg
That is the "correct" one from plot, with the higest value on y showing
at 18.
1997 Apr 08
2
R-alpha: CRAN source/contrib
I've put all ``current'' add-on packages into CRAN's source/contrib tree
and created an INDEX file (attached below). As you can see, currently
we have
acepack
bootstrap
ctest
date
e1071
fracdiff
gee
jpn
snns
splines
survival4
(Yes, e1071 and jpn are new ... more on the latter in a later mail.)
In the near future, I am hoping for the following:
oz (Bill
2005 Aug 19
4
Advice about system for installing & updating all R package in a Linux Lab?
Good day:
I'm administering 6 linux systems (FC4) in a student lab and worry that
users may want packages that are not installed. I get tired of adding
them one by one. Then I happened upon this page
http://support.stat.ucla.edu/view.php?supportid=30
about installing all R packages from CRAN. That did not run as it was,
but after some fiddling I arrived at the following script, which
2000 Mar 27
1
R port of acepack
To whom should bug reports of the R port of acepack be directed?
On a SPARC/Solaris 2.6 or 2.7 (SunOS 5.6 or 5.7) system running
R-1.0.0 the avas example fails
> library(acepack)
> example(avas)
avas> TWOPI <- 8 * atan(1)
avas> x <- runif(200, 0, TWOPI)
avas> y <- exp(sin(x) + rnorm(200)/2)
avas> a <- avas(x, y)
Process R bus error (core dumped) at Mon
2007 May 10
1
Follow-up about ordinal logit with mixtures: how about 'continuation ratio' strategy?
This is a follow up to the message I posted 3 days ago about how to
estimate mixed ordinal logit models. I hope you don't mind that I am
just pasting in the code and comments from an R file for your
feedback. Actual estimates are at the end of the post.
### Subject: mixed ordinal logit via "augmented" data setup.
### I've been interested in estimating an ordinal logit model
2001 Oct 18
0
Numerical precision of hist densities or cumsum?
Today I wanted to experiment with different distributions an to see the
hazard rates they imply. So I eventually ended up with this, which uses
the hist object's handy $density and the cumsum function in R:
x <- c(rweibull(21000,0.5,0.7))
#create "breaks" vector to go into histogram
#need last break bigger than max(x)
y <- seq(0,max(x)+2)
histx <-
2005 Jun 16
1
Analysing ordinal/nominal data
Hi!
I'm looking for a solution to analyse data, which consists of
dichotomous responses (yes/no) for 2 multinomial ordinal variables. I
was trying glm() and got hierarhical models treating all variables as
nominal, but I can't figure out how to tell glm() to use a model for
ordinal data like this:
log(Mij) = intercept + X + Y + Z + beta*(x-x')*(y-y')
where beta is a