Displaying 20 results from an estimated 5000 matches similar to: "Count number of different patterns (Polytomous variable)"
2010 Mar 24
3
How to use the paste function to create an already used variable
Hi there,
I have the following problem
Four data frames exist:
data1
data2
data3
data4
Now I want to write a loop and temporarily store the data1, data2,
data3, data4 in a variable called data.
I tried the following...
for (i in 1:4) {
Data <- paste("data",i,sep="")
...
..
}
but it doesn't function. I think the problem is the definition of the
mode of the pasted
2009 Sep 08
1
cbind formula definition
Hi there,
I have the following problem:
I have a package called "polLCA" which has the following syntax:
poLCA(formula, data)
and needs the following formula definition:
formula <- cbind(V1,V2,V3,...)
So far so good.
What I tried now was the following:
#Get "data" with the "read.table" fuction
data <- read.table("d:/ .....)
#Select cols to use in the
2012 Jun 16
2
How to specify "newdata" in a Cox-Modell with a time dependent interaction term?
Dear Mr. Therneau, Mr. Fox, or to whoever, who has some time...
I don't find a solution to use the "survfit" function (package:
survival) for a defined pattern of covariates with a Cox-Model
including a time dependent interaction term. Somehow the definition of
my "newdata" argument seems to be erroneous.
I already googled the problem, found many persons having the
2005 Jan 07
2
help with polytomous logistic regression
Hi!
I'm trying to do some ploytomous logistic regression using multinom() in the nnet package, but am a bit confused about interpretation of the results
Is it possible to get the following quantities:
I: maximum likelihood estimates to test for fit of model and significance of each predictor
(I would like to produce a table of the following type)
Analysis of Variance: MLE (values are
2010 Nov 13
1
Define a glm object with user-defined coefficients (logistic regression, family="binomial")
Hi there,
I just don't find the solution on the following problem. :(
Suppose I have a dataframe with two predictor variables (x1,x2) and one
depend binary variable (y). How is it possible to define a glm object
(family="binomial") with a user defined logistic function like p(y) =
exp(a + c1*x1 + c2*x2) where c1,c2 are the coefficents which I define.
So I would like to do no
2011 Aug 21
2
Increase the size of the boxes but not the text in a legend
HI there,
I want to add a legend to a plot using the density and angle argument,
so patterns with lines in different angles are used in the plot and
should be referred to.
When I use default settings, the filled boxes are too small.
With the cex argument I can enlarge the whole legend, but then the text
gets too big.
How could I just increase the size of the single boxes and not the text.
I
2011 Apr 29
1
logistic regression with glm: cooks distance and dfbetas are different compared to SPSS output
Hi there,
I have the problem, that I'm not able to reproduce the SPSS residual
statistics (dfbeta and cook's distance) with a simple binary logistic
regression model obtained in R via the glm-function.
I tried the following:
fit <- glm(y ~ x1 + x2 + x3, data, family=binomial)
cooks.distance(fit)
dfbetas(fit)
When i compare the returned values with the values that I get in SPSS,
2001 Nov 05
2
Item Response Analysis
Hello,
Would someone have ever heard or developed any Item Response Models library
for R ? Of course, a Rasch model can be estimated through glm() but it is not
the case for more complex (polytomous) response models.
Similarly I would be interested in any R implementation of nonlinear
multivariate analyses a la GIFI (HOMALS, PRINCALS, OVERALS).
Thanks a lot in advance,
Yvonnick Noel, PhD.
2009 Oct 15
1
"Complex?" import of pdf files (criminal records) into R table
Hi there,
I'm facing the decision if it would be possible to transform several
more or less complex pdf files into an R Table-Format or if it has to be
done manually. I think it would be a impudent to expect a complete
solution, but I would be grateful if anyone could give me an advice on
how the structure of such a R-program could look like, and if it's
possible in general.
Here
2010 Jul 23
2
glm - prediction of a factor with several levels
Dear community,
I'm currently attempting to predict the occurence of an event (factor)
having more than 2 levels with several continuous predictors. The model
being ordinal, I was waiting the glm function to return several intercepts,
which is not the case when looking to my results (I only have one
intercept). I finally managed to perform an ordinal polytomous logisitc
regression with the
2011 Jun 28
5
Memory Page Sharing on Xen 4.0.1
Dear List,
I?m trying to figure out *memory page sharing***using HVM on Xen 4.0.1,
but I?m not really able to find some useful information or sources about
this issue.
I just found two links porviding these sources:
http://knol.google.com/k/learning-grant-tables
http://blog.chinaunix.net/space.php?uid=20286427&do=blog&id=109114
Both are not working.. I think they are made for an older
2007 Oct 17
2
Problems with paste and blank
Hi there,
I've got the following problem under Windows XP, R 2.5.1:
When I'm pasting some objects:
Stadtwerksname<-"Mannheim"
Laufwerk<-"C:\\"
paste(Laufwerk,Stadtwerksname,".csv")
I get the result:
[1] "C:\\ Mannheim .csv"
The problem's are the superfluous gaps/blanks between the three parts.
Is there a way to get rid off this
2002 May 03
3
Regression models for ordinal responses ??
Hello list,
Is there any mean to fit models for ordinal response other than multinomial
polytomous ("multinom" from nnet ) and cumulative logit ("polr" from MASS)?
I am particularly interested in continuation-ratio model and
adjacent-category logit model. It is for the sake of epidemiology in
wild-living populations!
Many thanks,
Emmanuelle Fromont
2001 Nov 13
1
models for polytomous data
Hi all
I have a dataset whose response is a categorical variable of the
ordinal scale type (6 levels).
I'm interested in building classification models, and I'm wondering if
there is something implemented in R (or its packages) that I'm not aware
of, to treat the ordinal scale measurements straightforwardly. I can think
of the alternative of building a conditional (hierarchical)
2003 Mar 31
2
point-biserial correlation
Dear list,
has anyone written a package/function in R for computing a point-
biserial resp. biserial correlation?
Thanks in advance
Bernd
1997 Dec 10
1
R-beta: Logistic regression....
Dear R-users
I am introducing my collegue to R and she is interested
to use R to perform Polytomous Logistic Regression
called also Multi-category logistic regression. Is there
any program in R doing this?
Thank you so much for any feedback.
I take this opportunity to thank people who were kind to answer my
query about how to include a postscript file generated from R, in a
latex
file and
2007 May 10
1
anyone konw Polyclass package in R?
Hi everyone:
Polyclass is a polytomous logistic regression model using
linear splines and their tensor products. It provides estimates for
conditional class probabilities which can then be used to predict class
labels. I know there is Polyclass package in S-plus. So I'm wondering if
there is a corresponding package in R? I have been searching for it for
quite a while, but still
2009 Apr 24
1
ordinal logistic regression for longitudinal data set
Hi,
Can one tell me which procedure will fit an ordinal logistic regression
model for longitudinal data set.
To be precise, I have both dichotomous and polytomous items. Also, I
would like to specify different covariance structures (unstructured, ar1
etc) for trial runs.
Thanks
--
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2000 Mar 10
1
logit and polytomous data
I am new to generalized linear models and studying
McCullagh & Nelder (1989). Especially, I have a problem
resembling the \"cheese taste\" example (5.3.1. p. 109) of
the book. I tried to analyse the cheese example with R but
failed to do so because R allowed me to use logit link
function only with binary family that supposes 0 <= y <= 1.
Do I need to scale the y\'s or
2005 May 13
1
multinom(): likelihood of model?
Hi all,
I'm working on a multinomial (or "polytomous") logistic regression
using R and have made great progress using multinom() from the nnet
library. My response variable has three categories, and there are two
different possible predictors. I'd like to use the likelihoods of
certain models (ie, saturated, fitteds, and null) to calculate
Nagelkerke R-squared values for