similar to: mixed model question and using lmer

Displaying 20 results from an estimated 20000 matches similar to: "mixed model question and using lmer"

2009 Apr 18
1
Modelling an "incomplete Poisson" distribution ?
Dear list, I have the following problem : I want to model a series of observations of a given hospital activity on various days under various conditions. among my "outcomes" (dependent variables) is the number of patients for which a certain procedure is done. The problem is that, when no relevant patient is hospitalized on said day, there is no observation (for which the "number
2008 Feb 05
1
Extracting level-1 variance from lmer()
All, How does one extract the level-1 variance from a model fit via lmer()? In the code below the level-2 variance component may be obtained via subscripting, but what about the level-1 variance, viz., the 3.215072 term? (actually this term squared) Didn't see anything in the archives on this. Cheers, David > fm <- lmer( dv ~ time.num*drug + (1 | Patient.new), data=dat.new )
2007 Jul 06
1
maintaining specified factor contrasts when subsetting in lmer
All, I'm using lmer for some repeated measures data and have specified the contrasts for a time factor such that say time 3 is the base. This works fine. However, when I next use the subset argument to remove the last two time values, the output indicates that the specified contrast is not maintained (see below). I can solve this by creating a new dataframe for the subset of interest
2007 Feb 14
1
nested model: lme, aov and LSMeans
I'm working with a nested model (mixed). I have four factors: Patients, Tissue, sex, and tissue_stage. Totally I have 10 patients, for each patient, there are 2 tissues (Cancer vs. Normal). I think Tissue and sex are fixed. Patient is nested in sex,Tissue is nested in patient, and tissue_stage is nested in Tissue. I tried aov and lme as the following, > aov(gene ~ tissue + gender +
2006 May 15
1
anova statistics in lmer
Dear list members, I am new to R and to the R-help list. I am trying to perform a mixed-model analysis using the lmer() function. I have a problem with the output anova table when using the anova() function on the lmer output object: I only get the numerator d.f., the sum of squares and the mean squares, but not the denominator d.f., F statistics and P values. Below is a sample output, following
2007 Aug 16
4
residual plots for lmer in lme4 package
Hi, I was wondering if I might be able to ask some advice about doing residual plots for the lmer function in the lme4 package. Our group's aim is to find if the expression staining of a particular gene in a sample (or "core") is related to the pathology of the core. To do this, we used the lmer function to perform a logistic mixed model below. I apologise in advance
2008 Mar 08
1
analysing mixed effects/poisson/correlated data
I am attempting to model data with the following variables: timepoint - n=48, monthly over 4 years hospital - n=3 opsn1 - no of outcomes total.patients skillmixpc - skill mix percentage nurse.hours.per.day Aims To determine if skillmix affects rate (i.e. no.of.outcomes/total.patients). To determine if nurse.hours.per.day affects rate. To determine if rates vary between
2012 Jul 20
1
Extracting standard errors for adjusted fixed effect sizes in lmer
Dear R help list, I have done a lot of searching but have not been able to find an answer to my problem. I apologize in advance if this has been asked before. I am applying a mixed model to my data using lmer. I will use sample data to illustrate my question: >library(lme4) >library(arm) >data("HR", package = "SASmixed") > str(HR) 'data.frame': 120 obs.
2005 May 04
1
lmer error:flist must be a non-empty list
Hi, I was wondering if anyone could give me advice regarding using the lmer command in lme4 package to do logistic regression (mixed effects model). I use the following command lmer(ISH ~ArrayPathology2, random=~1|PatientID, data=HSDB4.noNA, family="binomial") where ISH is outcome(0 or 1), ArrayPathology2 is the variable of interest(factor), PatientID is random effect(factor), and
2011 Aug 16
1
Repeated measures cummulative logit mixed model
Dear R help gurus, I have the following problem and I would be delighted if you could help me. >From a large (1500) cohort of patients we have been taking some measurements (ECG measurements, but its not important). The measurements are ordinal in 4 grades (Grade I-IV, grade IV being the most severe form). Every patients has been measured several times (usually once per year). The
2006 Sep 26
2
treatment effect at specific time point within mixed effects model
All, The code below is for a pseudo dataset of repeated measures on patients where there is also a treatment factor called "drug". Time is treated as categorical. What code is necessary to test for a treatment effect at a single time point, e.g., time = 3? Does the answer matter if the design is a crossover design, i.e, each patient received drug and placebo? Finally, what would
2012 Feb 06
1
multiple comparisons in nested design
Dear professors and collegues I need to perform a analysis of dates from a nested experimental design. From "Bioestatical Analysis" of Zar "Bimetry of Sokal" & Rohlf "Design and Analysis of Experiments" of Montgomery I have: Sum (mean(x)_i - mean(x)_T)2 / (a-1) -> var(epsilon) + n sigma2_B + n b (sum alfa_i)2 / (a-1) Sum (mean(x)_ij - mean(x)_i)2 /
2007 Dec 18
1
How can I extract the AIC score from a mixed model object produced using lmer?
I am running a series of candidate mixed models using lmer (package lme4) and I'd like to be able to compile a list of the AIC scores for those models so that I can quickly summarize and rank the models by AIC. When I do logistic regression, I can easily generate this kind of list by creating the model objects using glm, and doing: > md <- c("md1.lr", "md2.lr",
2008 Sep 14
2
Help please! How to code a mixed-model with 2 within-subject factors using lme or lmer?
Hello, I'm using aov() to analyse changes in brain volume between males and females. For every subject (there are 331 in total) I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). The data looks like this: Subject Sex Lobe Tissue Volume subect1 1 F g 262374 subect1 1 F w 173758 subect1 1 O g 67155 subect1 1 O w 30067 subect1 1 P g 117981
2009 Mar 10
1
help structuring mixed model using lmer()
Hi all, This is partly a statistical question as well as a question about R, but I am stumped! I have count data from various sites across years. (Not all of the sites in the study appear in all years). Each site has its own habitat score "habitat" that remains constant across all years. I want to know if counts declined faster on sites with high "habitat" scores. I can
2006 Oct 20
1
Translating lme code into lmer was: Mixed effect model in R
This question comes up periodically, probably enough to give it a proper thread and maybe point to this thread for reference (similar to the 'conservative anova' thread not too long ago). Moving from lme syntax, which is the function found in the nlme package, to lmer syntax (found in lme4) is not too difficult. It is probably useful to first explain what the differences are between the
2010 Oct 31
1
Need help with lmer model specification syntax for nested mixed model
I haven't been able to fully make sense of the conflicting online information about whether and how to specify nesting structure for a nested, mixed model. I'll describe my experiment and hopefully somebody who knows lme4 well can help. We're measuring the fluorescence intensity of brain slices from frogs that have undergone various treatments. We want to use multcomp to look for
2012 Mar 13
1
how to write crossed and nested random effects in a model
Dear R Users, I have a question based on my research. I am analyzing reader-based diagnostic data set. My study involves diabetic patients who were evaluated for treatable diabetic retinopathy based on the presence or absence of two pathologies in their eyes. Pathologies were identified using the clinical examination (Gold standard method). In addition it can be identified by taking digital
2009 Oct 15
2
plotting/examining residuals of a mixed generalised linear model
Dear R users, I'm hoping that more experienced users will be able to assist me in examining the model fit of a mixed generalised linear model. The example using the data 'bacteria' within the MASS package will hopefully illustrate what I would like to acheive; library(MASS) library(nlme) attach(bacteria) # y being output and the trt - treatment group being an explanatory variable.
2006 Nov 16
4
lme4 package: Fitted values and residuals
Dear all, I have three concerns: 1) I am running models with the lme4 package. I cannot find a way to pull out a vector of the fitted values and the residuals. Does anybody know how to do it? 2) How can I nest a random effect variable into a "two-level" fixed effect variable? 3) Suppose I have the following model: y = a + b|c + d + error, where 'a' is a fixed effect, 'c'