Displaying 20 results from an estimated 3000 matches similar to: "lme - Random Effects Struture"
2012 Sep 21
1
translating SAS proc mixed into R lme()
Dear R users,
I need help with translating these SAS codes into R with lme()? I have a
longitudinal data with repeated measures (measurements are equally spaced
in time, subjects are measured several times a year). I need to allow slope
and intercept vary.
SAS codes are:
proc mixed data = survey method=reml;
class subject var1 var3 var2 time;
model score = var2 score_base var4 var5 var3
2004 Oct 25
0
答复: Multiple formula in one block
Hi Dimitris:
Thanks for your help, I will try.
BR
Yiyao
-----ÔʼÓʼþ-----
·¢¼þÈË: Dimitris Rizopoulos [mailto:dimitris.rizopoulos at med.kuleuven.ac.
be]
·¢ËÍʱ¼ä: 2004Äê10ÔÂ25ÈÕ 15:39
ÊÕ¼þÈË: YiYao_Jiang
³ËÍ: r-help at stat.math.ethz.ch
Ö÷Ìâ: Re: [R] Multiple formula in one block
Hi YiYao,
you need the `?panel.abline()' function, somehing like:
panel=function(x, breaks,
2008 Feb 28
0
problem with the ltm package - 3PL model
Hi Xavier,
the reason you observe this feature is that in the 'constraint'
argument you should specify the values under the additive
parameterization, i.e., when in the second column of the matrix
supplied in 'constraint' you specify 2, then you need to provide the
easiness parameters (not the difficulty parameters) in the third
column. Check the Details section of ?tpm() and
2005 Sep 05
0
New package for grouped data models
Dear R-users,
We'd like to announce the release of our new package "grouped"
(available from CRAN), for fitting models for grouped or coarse data,
under the Coarsened At Random assumption. This is useful in cases
where the true response variable is known only up to an interval in
which it lies. Features of the package include: power calculations for
two-group comparisons,
2005 Sep 05
0
New package for grouped data models
Dear R-users,
We'd like to announce the release of our new package "grouped"
(available from CRAN), for fitting models for grouped or coarse data,
under the Coarsened At Random assumption. This is useful in cases
where the true response variable is known only up to an interval in
which it lies. Features of the package include: power calculations for
two-group comparisons,
2004 Aug 09
1
Follow-up Q Re: displaying computation outputs inside "for" loops
I have a somewhat related question. A while back I was doing some simulations
using for() loops, and I wanted to keep track of the iterations using a line of
code quite similar to what Dimitris presented below. Instead of printing the
iteration message at the end of each iteration (actually, at the end of every
100th), nothing was printed until the for() loop was complete, and *then* all
2008 Feb 20
0
New Package 'JM' for the Joint Modelling of Longitudinal and Survival Data
Dear R-users,
I'd like to announce the release of the new package JM (JM_0.1-0
available from CRAN) for the joint modelling of longitudinal and
time-to-event data.
The package has a single model-fitting function called jointModel(),
which accepts as main arguments a linear mixed effects object fit
returned by function lme() of package nlme, and a survival object fit
returned by either
2008 Feb 20
0
New Package 'JM' for the Joint Modelling of Longitudinal and Survival Data
Dear R-users,
I'd like to announce the release of the new package JM (JM_0.1-0
available from CRAN) for the joint modelling of longitudinal and
time-to-event data.
The package has a single model-fitting function called jointModel(),
which accepts as main arguments a linear mixed effects object fit
returned by function lme() of package nlme, and a survival object fit
returned by either
2006 May 12
3
Maximum likelihood estimate of bivariate vonmises-weibulldistribution
Thanks Dimitris!!! That's much clearer now. Still have a lot of work to
do this weekend to understand every bit but your code will prove very
useful.
Cheers,
Aziz
-----Original Message-----
From: Dimitrios Rizopoulos [mailto:Dimitris.Rizopoulos at med.kuleuven.be]
Sent: May 12, 2006 4:35 PM
To: Chaouch, Aziz
Subject: RE: [R] Maximum likelihood estimate of bivariate
2006 Mar 13
0
package ltm -- version 0.4-0
Dear R-users,
I'd like to announce the new version of package 'ltm' for Item
Response Theory analysis. The function grm() (along with supporting
methods, i.e., anova, margins, factor.scores, etc.) has been added for
fitting the Graded Response Model for ordinal polytomous manifest
variables. An extra feature of the plot method for classes 'grm',
'ltm' and
2006 Mar 13
0
package ltm -- version 0.4-0
Dear R-users,
I'd like to announce the new version of package 'ltm' for Item
Response Theory analysis. The function grm() (along with supporting
methods, i.e., anova, margins, factor.scores, etc.) has been added for
fitting the Graded Response Model for ordinal polytomous manifest
variables. An extra feature of the plot method for classes 'grm',
'ltm' and
2005 Sep 27
0
package 'ltm' -- version: 0.3-0
Dear R users,
I'd like to announce the new version of the package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch and
two-parameter logistic models) under the Item Response Theory
approach. Three main extra features have been added: (i) now both
ltm() and rasch() permit general fixed-value constraints (e.g., useful
for scaling purposes), (ii)
2005 Sep 27
0
package 'ltm' -- version: 0.3-0
Dear R users,
I'd like to announce the new version of the package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch and
two-parameter logistic models) under the Item Response Theory
approach. Three main extra features have been added: (i) now both
ltm() and rasch() permit general fixed-value constraints (e.g., useful
for scaling purposes), (ii)
2006 Sep 06
0
package ltm -- version 0.6-0
Dear R-users,
I'd like to announce the release of the new version of package 'ltm'
for analyzing multivariate dichotomous and polytomous data under the
Item Response Theory approach.
New features:
* function tpm() (along with supporting methods, i.e., anova, plot,
margins, factor.scores, etc.) has been added for fitting Birnbaum's
Three Parameter Model.
* grm() can now
2006 Sep 06
0
package ltm -- version 0.6-0
Dear R-users,
I'd like to announce the release of the new version of package 'ltm'
for analyzing multivariate dichotomous and polytomous data under the
Item Response Theory approach.
New features:
* function tpm() (along with supporting methods, i.e., anova, plot,
margins, factor.scores, etc.) has been added for fitting Birnbaum's
Three Parameter Model.
* grm() can now
2005 Jan 21
2
chi-Squared distribution in Friedman test
Dear R helpers:
Thanks for the previous reply. I am using Friedman racing test. According the the book "Pratical Nonprametric Statistic" by WJ Conover, after computing the statistics, he suggested to use chi-squared or F distribution to accept or reject null hypothesis. After looking into the source code, I found that R uses chi-sqaured distribution as below:
PVAL <-
2006 Jan 10
2
graphics pages?
Dear R People:
In S Plus, if you have a function which calls the plot
function several times, you get several "pages" of graphics
output.
Is there an eqivalent in R, please?
R version 2.2.1 windows
Thanks in advance!
Sincerely,
Erin Hodgess
Associate Professor
Department of Computer and Mathematical Sciences
University of Houston - Downtown
mailto: hodgess at gator.uhd.edu
2004 Oct 06
1
dlogis for large negative numbers
Hi to all,
> dlogis(-2000)
[1] NaN
Warning message:
NaNs produced in: dlogis(x, location, scale, log)
> dnorm(-2000)
[1] 0
Is this an expected behaviour of `dlogis()'?
Thanks in advance for any comments,
Dimitris
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major 1
minor 9.1
2005 Mar 15
0
New package for latent trait models
Dear R-users,
I'd like to announce the release of my new package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch
model) under the Item Response Theory approach. The latent trait model
is the analogous of the factor analysis model for Bernoulli response
data. "ltm" fits the linear one- and two-factor models but also allows
for
2005 Mar 15
0
New package for latent trait models
Dear R-users,
I'd like to announce the release of my new package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch
model) under the Item Response Theory approach. The latent trait model
is the analogous of the factor analysis model for Bernoulli response
data. "ltm" fits the linear one- and two-factor models but also allows
for