Hallo,
i am trying to use the mlogit package (which uses the multinom package
according to the documentation)
the multinom function works fine:
> fsex = multinom(country ~ sex, data=included_s_sex_MF)
# weights: 66 (42 variable)
initial value 8222.172926
iter 10 value 7647.481298
iter 20 va
On Thu, 2008-07-31 at 10:31 -0500, Marc Schwartz wrote:
> on 07/31/2008 07:40 AM Wim Bertels wrote:
> > On Wed, 2008-07-30 at 12:13 -0500, Marc Schwartz wrote:
> >> on 07/30/2008 08:48 AM Wim Bertels wrote:
> >>> Hi,
> >>>
> >>> does anyone k
On Wed, 2008-07-30 at 12:13 -0500, Marc Schwartz wrote:
> on 07/30/2008 08:48 AM Wim Bertels wrote:
> > Hi,
> >
> > does anyone know of a function to calculate odds ratios in multiway
> > tables (stratified) (+ the other usual statistics involved)
> >
> >
Hi,
does anyone know of a function to calculate odds ratios in multiway
tables (stratified) (+ the other usual statistics involved)
i mean:
say we have a table r*c*d,
For every d (depth) we have a r*c table,
and in this table the odds ratio's are calculated for every 2*2 subtable
in it.
logicall
Thanks for the quick reply David,
so far this sums up to:
# logistic on binary data
lrm combined with resid(model,'gof')
# logistic on raw binary data
glm with gof using anova.glm
(i think that anova.glm only makes sence on grouped binary data, not on the raw binary data..)
(so what is the g
Hallo,
which function can i use to do (baseline) logistic regression +
goodness
of fit tests?
so far i found:
# logistic on binary data
lrm combined with resid(model,'gof')
# logistic on binary dat
Hi Neil,
as i am not an advanced user,
i find reference cards very handy
(google: reference card R)
hth a bit,
Wim
Message: 70
Date: Wed, 28 May 2008 15:25:36 -0500
From: "Neil Gupta" <[EMAIL PROTECTED]>
Subject: [R] R reference Books
To: R-help@r-project.org
Message-ID:
<[EMAIL PROTEC
Hallo,
i tried writing a function to extract
all the odds ratio's from a ftable:
(+ p.adjust needs to build in)
So i tried the following:
ORCalcul <- function(m) {
or<-matrix(1:(length(m[,1])-1)*(length(m[1,])-1)*5,length(m[,1])-1,length(m[1,])-1)
for(i in 1:length(m[,1])-1) {
Hallo,
i get a warning message that NAs are introduced by coercion,
so my idea is to write a function to see which values are turned into
NA
For this i need to write a function to go through (loop) the original
data and the transformed (with the introduced na) to see which data were
transformed
9 matches
Mail list logo
