Displaying 20 results from an estimated 6000 matches similar to: "Specify multiple nested random effects in lme with heteroskedastic variance across group"
2005 Feb 14
1
testing equality of variances across groups in lme?
Hello. I am fitting a two-level mixed model which assumes equality of
variance in the lowest-level residuals across groups. The call is:
fit3<-lme(CLnNAR~CLnRGR,data=meta.analysis,
+ na.action="na.omit",random=~1+CLnRGR|study.code)
I want to test the assumption of equality of variances across groups at
the lowest level. Can someone tell me how to do this? I know that one
2010 Mar 22
0
using lmer weights argument to represent heteroskedasticity
Hi-
I want to fit a model with crossed random effects and heteroskedastic
level-1 errors where inferences about fixed effects are of primary
interest. The dimension of the random effects is making the model
computationally prohibitive using lme() where I could model the
heteroskedasticity with the "weights" argument. I am aware that the weights
argument to lmer() cannot be used to
2010 Oct 04
1
Fixed variance structure for lme
I have a data set with 50 different x values and 5 values for the sampling
variance; each of the 5 sampling variances corresponds to 10 particular x
values. I am trying to fit a mixed effect linear model and I'm not sure
about the syntax for specifying the fixed variance structure. In Pinheiro's
book my situation appears to be similar to the example used for varIdent,
where there is a
2007 Jan 02
1
How to extract the variance componets from lme
Here is a piece of code fitting a model to a (part) of a dataset, just
for
illustration. I can extract the random interaction and the residual
variance
in group meth==1 using VarCorr, but how do I get the other residual
variance?
Is there any way to get the other variances in numerical form directly -
it
seems a litte contraintuitive to use "as.numeric" when extracting
estimates,
2004 Jul 12
2
lme unequal random-effects variances varIdent pdMat Pinheiro Bates nlme
How does one implement a likelihood-ratio test, to test whether the
variances of the random effects differ between two groups of subjects?
Suppose your data consist of repeated measures on subjects belonging to
two groups, say boys and girls, and you are fitting a linear mixed-effects
model for the response as a function of time. The within-subject errors
(residuals) have the same variance in
2006 Mar 07
1
lme and gls : accessing values from correlation structure and variance functions
Dear R-users
I am relatively new to R, i hope my many novice questions are welcome.
I have problems accessing some objects (specifically the random effects, correlation structure and variance function) from an object of class gls and lme.
I used the following models:
yah <- gls (outcome~ -1 + as.factor(Trial):as.factor(endpoint)+
2007 Mar 05
1
Heteroskedastic Time Series
Hi R-helpers,
I'm new to time series modelling, but my requirement seems to fall just
outside the capabilities of the arima function in R. I'd like to fit an
ARMA model where the variance of the disturbances is a function of some
exogenous variable. So something like:
Y_t = a_0 + a_1 * Y_(t-1) +...+ a_p * Y_(t-p) + b_1 * e_(t-1) +...+ b_q *
e_(t-q) + e_t,
where
e_t ~ N(0, sigma^2_t),
USING TOBIT OR WHAT ALTERNATIVE WHEN DATA ARE PANEL AND HETEROSKEDASTIC AND PROBABLY AUTOCORRELATED?
2008 Aug 28
0
USING TOBIT OR WHAT ALTERNATIVE WHEN DATA ARE PANEL AND HETEROSKEDASTIC AND PROBABLY AUTOCORRELATED?
Please, I seek expertise and advice, possibly leads to R packages or
stats literature.
My data: measurements of economic variables for each county of
California over 37 years.
My dependent variable is square feet of office floor space permitted to
be added in a county.
Independent variables include for example change in number of office
jobs in same county same year (and lagged years).
2006 Nov 09
1
Variance Functions in lme
Using the weight argument with a variance function in lme (nlme), you
can allow for heteroscedasticity of the within-group error. Is there a
way to do this for the other variance components? For example, suppose
you had subjects, days nested within subjects, and visits nested within
days within subjects (a fully nested two-way design) and you had, say
men and women subjects. Could you allow for
2007 Jun 28
1
unequal variance assumption for lme (mixed effect model)
Dear Douglas and R-help,
Does lme assume normal distribution AND equal variance among groups
like anova() does? If it does, is there any method like unequal
variance T-test (Welch T) in lme when each group has unequal variance
in my data?
Thanks,
Shirley
2007 Jun 01
2
how to specify starting values in varIdent() of lme()
I was reading the help but just did not get how to specify starting values for
varIdent() of the lme() function, although I managed to do it for corSymm().
Do I specify the values just as they are printed out in an output, like c(1,
1.3473, 1.0195). Or do I need to take the residual and multiply it with these
like c(0.2235, 0.2235*1.3473, 0.2235*1.0195)
or any other form that I dont know of?
2007 Nov 12
1
Using lme (nlme) to find the conditional variance of the random effects
Using lmer in the lme4 package, you can compute the conditional
variance-covariance matrix of the random effects using the bVar slot:
bVar: A list of the diagonal inner blocks (upper triangles only) of the
positive-definite matrices on the diagonal of the inverse of ZtZ+Omega.
With the appropriate scale factor (and conversion to a symmetric matrix)
these are the conditional variance-covariance
2007 Mar 06
0
different random effects for each level of a factor in lme
I have an interesting lme - problem. The data is part of the Master
Thesis of my friend, and she had some problems analysing this data,
until one of her Jurors proposed to use linear mixed-effect models. I'm
trying to help her since she has no experience with R. I'm very used to
R but have very few experience with lme.
The group calls of one species of parrot were recorded at many
2006 Sep 23
1
variance-covariance structure of random effects in lme
Dear R users,
I have a question about the patterned variance-covariance structure for the random effects in linear mixed effect model.
I am reading section 4.2.2 of "Mixed-Effects Models in S and S-Plus" by Jose Pinheiro and Douglas Bates.
There is an example of defining a compound symmetry variance-covariance structure for the random effects in a
split-plot experiment on varieties of
2006 Jun 01
1
setting the random-effects covariance matrix in lme
Dear R-users,
I have longitudinal data and would like to fit a model where both the variance-covariance matrix of the random effects and the residual variance are conditional on a (binary) grouping variable.
I guess the model would have the following form (in hierarchical notation)
Yi|bi,k ~ N(XiB+Zibi, sigmak*Ident)
bi|k ~ N(0, Dk)
K~Bernoulli(p)
I can obtain different sigmas (sigma0 and
2008 Jul 30
1
Mixed effects model where nested factor is not the repeated across treatments lme???
Hi,
I have searched the archives and can't quite confirm the answer to this.
I appreciate your time...
I have 4 treatments (fixed) and I would like to know if there is a
significant difference in metal volume (metal) between the treatments.
The experiment has 5 blocks (random) in each treatment and no block is
repeated across treatments. Within each plot there are varying numbers
of
2012 Jun 26
1
How to estimate variance components with lmer for models with random effects and compare them with lme results
Hi,
I performed an experiment where I raised different families coming from two
different source populations, where each family was split up into a
different treatments. After the experiment I measured several traits on each
individual.
To test for an effect of either treatment or source as well as their
interaction, I used a linear mixed effect model with family as random
factor, i.e.
2006 Sep 20
1
variance functions in glmmPQL or glm?
Hello R users-
I am new to R, and tried searching the archives and literature for an answer
to this - please be patient if I missed something obvious.
I am fitting a logistic regression model, and would like to include variance
functions (specifically the varIdent function). I cannot figure out how to
do this either in glmmPQL (or something similar) for the model with random
effects, or in glm
2002 Aug 29
8
lme() with known level-one variances
Greetings,
I have a meta-analysis problem in which I have fixed effects
regression coefficients (and estimated standard errors) from identical
models fit to different data sets. I would like to use these results
to create pooled estimated regression coefficients and estimated
standard errors for these pooled coefficients. In particular, I would
like to estimate the model
\beta_{i} = \mu +
2006 Jul 17
1
Variance functions in package nlme
Dear R-help,
I am trying to set up linear mixed effects models in R using the (recommended)
nlme package (R version 2.3.1 on a Linux platform). When trying to reproduce
an example from Jose Pinheiro & Douglas Bates (2000, p 210) I get the
following error message (code to produce message pasted as well):
library("nlme")
data("Orthodont")
vf1Ident <- varIdent(