Displaying 20 results from an estimated 10000 matches similar to: "A question on lmer() function"
2010 Jan 04
2
Piecewise regression in lmer
Dear all,
I'm attempting to use a piecewise regression to model the trajectory
of reproductive traits with age in a longitudinal data set using a
mixed model framework. The aim is to find three slopes and two points-
the slope from low performance in early age to a point of high
performance in middle age, the slope (may be 0) of the plateau from
the start of high performance to the
2010 Aug 26
1
Random slopes in lmer
Hi
I want to extract the random slopes from a lmer (I am doing a random regression), but are the answers obtained from ranef or coef?
My model is: mod1<-lmer(B~ A +(A|bird), family=quasibinomial)
And I want to obtain a slope for each individual bird but am not sure which output I need and can't find the answer anywhere.
Thanks
Sam
Dr Samantha Patrick
EU INTERREG Post Doc
Davy 618
2008 Apr 22
1
lmer model building--include random effects?
Hello,
This is a follow up question to my previous one http://tolstoy.newcastle.edu.au/R/e4/help/08/02/3600.html
I am attempting to model relationship satisfaction (MAT) scores
(measurements at 5 time points), using participant (spouseID) and
couple id (ID) as grouping variables, and time (years) and conflict
(MCI.c) as predictors. I have been instructed to include random
effects for the
2009 Aug 19
2
lmer with random slopes for 2 or more first-level factors?
I have data from a design in which items are completely nested within
subjects. Subject is the only second-level factor, but I have
multiple first-level factors (IVs). Say there are 2 such independent
variables that I am interested in. What is the proper syntax to fit a
mixed-effects model with a by-subject random intercept, and by-subject
random slopes for both the 2 IVs?
I can
2009 Aug 24
1
lme, lmer, gls, and spatial autocorrelation
Hello folks,
I have some data where spatial autocorrelation seems to be a serious
problem, and I'm unclear on how to deal with it in R. I've tried to do my
homework - read through 'The R Book,' use the online help in R, search the
internet, etc. - and I still have some unanswered questions. I'd greatly
appreciate any help you could offer. The super-super short explanation is
2008 Dec 17
1
Model building using lmer
Dear R-experts,
Quite new to R on this end, but learning fast (I hope).
I am running version 2.7.1 on Windows Vista. I have small dataset
which consists of:
# NestID: nest indicator for each chicken. Siblings sharing the same nest have the same nest indicator.
# Chick: chick indicator consisting of a unique ID for each single chick.
# Year: 1, 2.
# ClutchSize: 1-, 2- , 3-eggs.
# HO:
2010 Aug 18
1
what does it mean when my main effect 'disappears' when using lme4?
Hello,
Setup: I have data with ~10K observations. Observations come from 16
different laboratories (labs). I am interested in how a continuous factor,
X, affects my dependent variable, Y, but there are big differences in the
variance and mean across labs.
I run this model, which controls for mean but not variance differences
between the labs:
lm(Y ~ X + as.factor(labs)).
The effect of X is
2006 Jun 29
1
lmer - Is this reasonable output?
I'm estimating two models for data with n = 179 with four clusters (21,
70, 36, and 52) named siteid. I'm estimating a logistic regression model
with random intercept and another version with random intercept and
random slope for one of the independent variables.
fit.1 <- lmer(glaucoma~(1|siteid)+x1
+x2,family=binomial,data=set1,method="ML",
2009 Nov 24
2
random effects correlation in lmer
I am having an issue with lmer that I wonder if someone could explain.
I am trying to fit a mixed effects model to a set of longitudinal data
over a set of individual subjects:
(fm1 <- lmer(x ~ time + (time|ID),aa))
I quite often find that the correlation between the random effects is 1.0:
Linear mixed model fit by REML
Formula: x ~ time + (time | ID)
Data: aa
AIC BIC logLik deviance
2006 Apr 10
1
Random specification in LMER
Hello,
Can anybody help me understand the difference between the three different codes
in specifying the slope in the random part of a mixed model using LMER?
Here are the codes:
(age | id)
(1 + age | id)
(age - 1 | id)
Thank you in advance
Arnaud
2011 Jan 21
1
TRADUCING lmer() syntax into lme()
---------- Forwarded message ----------
From: Freddy Gamma <freddy.gamma@gmail.com>
Date: 2011/1/21
Subject: TRADUCING lmer() syntax into lme()
To: r-sig-mixed-models@r-project.org
Dear Rsociety,
I'd like to kingly ask to anyone is willing to answer me how to implement a
NON NESTED random effects structure in lme()
In particular I've tried the following translation from lmer to
2006 Aug 16
1
[SPAM] - RE: REML with random slopes and random intercepts giving strange results - Bayesian Filter detected spam
Can you provide the summary(m2) results?
> -----Original Message-----
> From: Simon Pickett [mailto:S.Pickett at exeter.ac.uk]
> Sent: Wednesday, August 16, 2006 7:14 AM
> To: Doran, Harold
> Cc: r-help at stat.math.ethz.ch
> Subject: [SPAM] - RE: [R] REML with random slopes and random
> intercepts giving strange results - Bayesian Filter detected spam
>
> Hi again,
2008 Aug 11
1
Simple lme/lmer random effects questions
Hello,
I have two very rudimentary questions regarding the random effects terms
in the lme and lmer functions. I apologize if this also partly strays
into a general statistics question, but I'm a bit new to this all. So
hopefully it'll be a quick problem to sort out...
Here is my experimental setup: I raised butterflies in 5 different
testing chambers all set to different
2005 Nov 01
3
glmmpql and lmer keep failing
Hello,
I'm running a simulation study of a multilevel model with binary
response using the binomial probit link. It is a random intercept and
random slope model. GLMMPQL and lmer fail to converge on a
*significant* portion of the *generated* datasets, while MlWin gives
reasonable estimates on those datasets. This is unacceptable. Does
anyone has similar experiences?
Regards,
Roel de
2006 Aug 10
1
help with structuring random factors using lmer()
Hi,
I am an R beginner and having problems structuring my REML models. I have
a model with
y=weight
x1=time
x2=timesquared
id=individual identity
I need to structure the model such that in the random effects there is a
constant intercept for all individuals but a separate individual slope for
both x1 and x2 (a coefficient score for every individual).
2010 Sep 10
1
lmer output
Hi
I have a question regarding an output of a binomial lmer-model.
The model is as follows:
lmer(y~diet * day * female + (day|female),family=binomial)
The corresponding output is:
Generalized linear mixed model fit by the Laplace approximation
Formula: y ~ diet * day * female + (day | female)
AIC BIC logLik deviance
1084 1136 -531.1 1062
Random effects:
Groups Name Variance
2009 Oct 29
1
singular variance-covariance warning in lmer
Dear R Users,
I was hoping for some help with a recurrent error message in lmer. I am trying to model the effect of temperature on metabolic rate in animals (response = int.length) at different temperatures (mean.sst), with repeated measurements on the same individuals (random effect = female). Ideally I would make a random slope and intercept model where the rate can change differently with
2006 Aug 24
1
lmer(): specifying i.i.d random slopes for multiple covariates
Dear readers,
Is it possible to specify a model
y=X %*% beta + Z %*% b ; b=(b_1,..,b_k) and b_i~N(0,v^2) for i=1,..,k
that is, a model where the random slopes for different covariates are i.i.d., in lmer() and how?
In lme() one needs a constant grouping factor (e.g.: all=rep(1,n)) and would then specify:
lme(fixed= y~X, random= list(all=pdIdent(~Z-1)) ) ,
that?s how it's done in the
2009 Apr 22
1
lmer() function
I'm trying to estimate a two-tier model with varying intercepts and slopes
across 20 groups, with each group having about 50 observations and with no
group predictor. I use the command lmer(y~x+(1+x | group)). But the result
is a constant intercept (zero standard deviation, all 20 intercept values
are the same). I'm puzzled; am I setting up my model wrong, or is the
algorithm
2006 Mar 08
1
Want to fit random intercept in logistic regression (testing lmer and glmmML)
Greetings. Here is sample code, with some comments. It shows how I
can simulate data and estimate glm with binomial family when there is
no individual level random error, but when I add random error into the
linear predictor, I have a difficult time getting reasonable estimates
of the model parameters or the variance component.
There are no clusters here, just individual level responses, so