Displaying 20 results from an estimated 2000 matches similar to: "scores from multinomial logistic regression"
2008 Jun 20
1
omnibus LR in multinomial model
If one estimates a model using multinom, is it possible to perform the
omnibus LR test ( the analogue to omnibus F in linear models ) using
the output
from multinom ? The residual deviance is there but I was hoping I could
somehow pull out the deviance based on just using an intercept ?
Sample code is below from the CAR book but I wasn't sure how to do it
based on that example. Thanks
2005 Nov 21
2
Multinomial Nested Logit package in R?
Dear R-Help,
I'm hoping to find a Multinomial Nested Logit package in R. It would
be great to find something analogous to "PROC MDC" in SAS:
> The MDC (Multinomial Discrete Choice) procedure analyzes models
> where the
> choice set consists of multiple alternatives. This procedure
> supports conditional logit,
> mixed logit, heteroscedastic extreme value,
2006 Feb 22
2
does multinomial logistic model from multinom (nnet) has logLik?
I want to get the logLik to calculate McFadden.R2 ,ML.R2 and
Cragg.Uhler.R2, but the value from multinom does not have logLik.So my
quetion is : is logLik meaningful to multinomial logistic model from
multinom?If it does, how can I get it?
Thank you!
ps: I konw VGAM has function to get the multinomial logistic model
with logLik, but I prefer use the function from "official" R
2012 Jan 05
2
difference of the multinomial logistic regression results between multinom() function in R and SPSS
Dear all,
I have found some difference of the results between multinom() function in
R and multinomial logistic regression in SPSS software.
The input data, model and parameters are below:
choles <- c(94, 158, 133, 164, 162, 182, 140, 157, 146, 182);
sbp <- c(105, 121, 128, 149, 132, 103, 97, 128, 114, 129);
case <- c(1, 3, 3, 2, 1, 2, 3, 1, 2, 2);
result <- multinom(case ~ choles
2003 Jan 24
3
Multinomial Logit Models
Hi
I am wanting to fit some multinomial logit models (multinom command in
package nnet)
Is it possible to do any model checking techniques on these models
e.g. residual, leverage etc. I cannot seem to find any commands that
will allow me to do this.
Many thanks
----------------------
L.E.Gross
L.E.Gross at maths.hull.ac.uk
2007 Jun 21
2
Multinomial models
Hello,
I am VERY new to R (one week) and I am trying to run a multinomial logit model.
The model I am using is
> model1 <- multinom(Y ~ X1 + X2 + , ..., Xn)
if I put in
> summary(model1)
I get
#Error in function (classes, fdef, mtable) :
unable to find an inherited method for function "fitted", for
signature "multinom"
and if I put in
> coef(model1)
2013 May 01
2
Factors and Multinomial Logistic Regression
Dear All,
I am trying to reproduce the example that I found online here
http://bit.ly/11VG4ha
However, when I run my script (pasted at the end of the email), I notice
that there is a factor 2 between the values for the coefficients for the
categorical variable female calculated by my script and in the online
example.
Any idea about where this difference comes from?
Besides, how can I
2007 Mar 26
1
fitted probabilities in multinomial logistic regression are identical for each level
I was hoping for some advice regarding possible explanations for the
fitted probability values I obtained for a multinomial logistic
regression. The analysis aims to predict whether Capgras delusions
(present/absent) are associated with group (ABH, SV, homicide; values
= 1,2,3,), controlling for previous violence. What has me puzzled is
that for each combination the fitted probabilities are
2013 May 24
1
Multinomial logistic regression
Is it possible to use function "glm" in case when my outcome variable has 5
different classes? I have seen examples only when using binomial outcome
variable.
What about using function "multinom"? How do I to get the signifigance and
the confidence levels of the coefficients and the value of goodness of the
model with this function?
Thank You for Your help!
--
View this
2003 Jun 03
1
Logistic regression problem: propensity score matching
Hello all.
I am doing one part of an evaluation of a mandatory welfare-to-work
programme in the UK.
As with all evaluations, the problem is to determine what would have
happened if the initiative had not taken place.
In our case, we have a number of pilot areas and no possibility of
random assignment.
Therefore we have been given control areas.
My problem is to select for survey individuals in
2005 Apr 12
1
factors in multinom function (nnet)
Dear All:
I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not.
I had posted earlier this example (thanks for the reply ronggui):
worms<- data.frame(year= rep(2000:2004, c(3,3,3,3,3)),age=rep(1:3,5),
2008 Nov 26
1
Estimates of coefficient variances and covariances from a multinomial logistic regression?
Hello and thanks in advance for any help,
I am using the 'multinom' function from the nnet package to calculate a
multinomial logistic regression. I would like to get a matrix estimates of
the estimated coefficient variances and covariances. Am I missing some
easy way to extract these?
Grant
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2003 Mar 27
4
Multinomial logistic regression under R and Stata
Dear Colleagues
I have been fitting some multinomial logistic regression models using R
(version 1.6.1 on a linux box) and Stata 7. Although the vast majority
of the parameter estimates and standard errors I get from R are the same
as those from Stata (given rounding errors and so on), there are a few
estimates for the same model which are quite different. I would be most
grateful if
2019 Jul 18
2
predict multinomial model con nnet
Hola todos
Cuando realizo las predicciones del modelo multinomial con el paquete nnet,
estas cambian cada vez que lo ejecuto ... saben por qué pasa esto ??
Gracias por la ayuda.
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2005 Apr 13
2
multinom and contrasts
Hi,
I found that using different contrasts (e.g.
contr.helmert vs. contr.treatment) will generate
different fitted probabilities from multinomial
logistic regression using multinom(); while the fitted
probabilities from binary logistic regression seem to
be the same. Why is that? and for multinomial logisitc
regression, what contrast should be used? I guess it's
helmert?
here is an example
2006 Sep 10
2
formatting data to be analysed using multinomial logistic regression (nnet)
I am looking into using the multinomial logistic regression option in the
nnet library and have two questions about formatting the data.
1. Can data be analysed in the following format or does it need to be
transformed into count data, such as the housing data in MASS?
Id Crime paranoia hallucinate toc disorg crimhist age
1 2 1 0 1 0 1 25
2 2 0 1 1 1 1 37
3 1 1 0 1 1 0 42
4 3 0
2009 Nov 27
0
Questions about use of multinomial for discrimination.
Dear All,
I am looking at discriminating among several individuals based on a few
variable sets (I think some variables do not make sense unless they are
entered together, so I "force" them into the models together, hence
datasets). I have done so with linear discriminant analysis (LDA) using
"MASS::lda", with acceptable results. However, one of my collaborators
2006 Jun 27
1
weights in multinom
Best R Help,
I like to estimate a Multinomial Logit Model with 10 Classes. The
problem is that the number of observations differs a lot over the 10
classes:
Class | num. Observations
A | 373
B | 631
C | 171
D | 700
E | 87
F | 249
G | 138
H | 133
I | 162
J | 407
Total: 3051
Where my data looks like:
x1 x2 x3 x4 Class
1 1,02 2 1 A
2 7,2 1 5 B
3 4,2 1 4 H
1 4,1 1 8 F
2 2,4 3 7 D
1 1,2 0 4 J
2 0,9
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
2005 Mar 09
1
plot(bclust) what is the 2nd plot?
Hi everyone,
Currently i'm trying to understand the bagged clustering algorithm, bclust
{e1071}.
When I run the given example in the help file (as below)
data(iris)
bc1 <- bclust(iris[,1:4], 3, base.centers=5)
plot(bc1)
and plot the bclust object, 2 graphs are produced.
The first is a dendrogram, but what is the second plot? The axes are not
labelled and what do the two