"Mixed models" refers to a class of models developed to account for correlation that may occur within nested data.
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5answers
15k views
What is the difference between fixed effect, random effect and mixed effect models?
In simple terms, how would you explain (perhaps with simple examples) the difference between fixed effect, random effect and mixed effect models?
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3answers
10k views
How to choose nlme or lme4 R library for mixed effects models?
I have fit a few mixed effects models (particularly longitudinal models) using lme4 in r but would like to really master the models and the code that goes with them.
However, before diving in with ...
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0answers
502 views
Variance on the sum of predicted values from a mixed effect model on a timeseries
I have a mixed effect model (in fact a generalized additive mixed model) that gives me predictions for a timeseries. To counter the autocorrelation, I use a corCAR1 model, given the fact I have ...
17
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1answer
4k views
What is compound symmetry in plain english?
I recently realized that a mixed-model with only subject as a random factor and the other factors as fixed factors is equivalent to an ANOVA when setting the correlational structure of the mixed model ...
17
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3answers
1k views
How to combine confidence intervals for a variance component of a mixed-effects model when using multiple imputation
The logic of multiple imputation (MI) is to impute the missing values not once but several (typically M=5) times, resulting in M completed datasets. The M completed datasets are then analyzed with ...
16
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2answers
316 views
Independence of residuals in a computer-based experiment/simulation?
I conducted a computer-based assessment of different methods of fitting a particular type of model used in the palaeo sciences. I had a large-ish training set and so I randomly (stratified random ...
16
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1answer
899 views
What are easy to interpret, goodness of fit measures for linear mixed effects models?
I am currently using the R package lme4.
I am using a linear mixed effects models with random effects:
...
16
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0answers
463 views
Computing repeatability of effects from an lmer model
I just came across this paper, which describes how to compute the repeatability (aka. reliability) of a measurement via mixed effects modelling. The R code would be:
...
15
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4answers
3k views
How do I fit a multilevel model for over-dispersed poisson outcomes?
I want to fit a multilevel GLMM with a Poisson distribution (with over-dispersion) using R. At the moment I am using lme4 but I noticed that recently the ...
15
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3answers
693 views
Interpreting three forms of a “mixed model”
There's a distinction that's tripping me up with mixed models, and I'm wondering if I could get some clarity on it. Let's assume you've got a mixed model of count data. There's a variable you know you ...
15
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2answers
431 views
How can I pool posterior means and credible intervals after multiple imputation?
I have used multiple imputation to obtain a number of completed datasets.
I have used Bayesian methods on each of the completed datasets to obtain posterior distributions for a parameter (a random ...
13
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4answers
13k views
Negative values for AICc (corrected Akaike Information Criterion)
I have calculated AIC and AICc to compare two general linear mixed models; The AICs are positive with model 1 having a lower AIC than model 2. However, the values for AICc are both negative (model 1 ...
13
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3answers
715 views
Pitfalls of linear mixed models
What are some of the main pitfalls of using linear mixed-effects models? What are the most important things to test/watch out for in assessing the appropriateness of your model? When comparing models ...
13
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2answers
2k views
How should mixed effects models be compared and or validated?
How are (linear) mixed effects models normally compared against each other? I know likelihood ratio tests can be used, but this doesn't work if one model is not a 'subset' of the other correct?
Is ...
13
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1answer
617 views
How should standard errors for mixed effects model estimates be calculated?
In particular, how should the standard errors of the fixed effects in a linear mixed effects model be calculated (in a frequentist sense)?
I have been lead to believe that the typical estimates ...
12
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3answers
1k views
Linear Mixed Effects Models
I have commonly heard that LME models are more sound in the analysis of accuracy data (i.e., in psychology experiments), in that they can work with binomial and other non-normal distributions that ...
12
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4answers
1k views
Follow up: In a mixed within-between ANOVA plot estimated SEs or actual SEs?
I am currently finishing a paper and stumbled upon this question from yesterday which led me to pose the same question to myself. Is it better to provide my graph with the actual standard error from ...
12
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4answers
901 views
Comparing mixed effect models with the same number of degrees of freedom
I have an experiment that I'll try to abstract here. Imagine I toss three white stones in front of you and ask you to make a judgment about their position. I record a variety of properties of the ...
12
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2answers
897 views
What is “restricted maximum likelihood” and when should it be used?
I have read in the abstract of this paper that
"The maximum likelihood (ML) procedure of Hartley aud Rao is modified by adapting a transformation from Pattersou and Thompson which partitions the ...
12
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2answers
483 views
What are the differences between “Mixed Effects Modelling” and “Latent Growth Modelling”?
I'm decently familiar with mixed effects models (MEM), but a colleague recently asked me how it compares to latent growth models (LGM). I did a bit of googling, and it seems that LGM is a variant of ...
11
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4answers
5k views
Using lmer for prediction
Hello
I have two problems that sound like natural candidates for multilevel/mixed models, which I have never used. The simpler, and one that I hope to try as an introduction, is as follows:
The data ...
11
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1answer
430 views
Variance partitioning and longitudinal changes in correlation with binary data
I am analysing data on 300,000 pupils in 175 schools with a logistic linear mixed effects model (random intercepts). Each pupil occurs exactly once and the data spans 6 years.
How do I partition ...
11
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2answers
531 views
Allowed comparisons of mixed effects models
I've been looking at mixed effects modelling using the lme4 package in R. I'm primarily using the lmer command so I'll pose my question through code that uses that ...
11
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1answer
5k views
When to use generalized estimating equations vs. mixed effects models?
I have been quite happily using mixed effects models for a while now with longitudinal data. I wish I could fit AR relationships in lmer (I think I'm right that I can't do this?) but I don't think ...
11
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1answer
292 views
Visualizing mixed model results
One of the problems I've always had with mixed models is figuring out data visualizations - of the kind that could end up on a paper or poster - once one has the results.
Right now, I'm working on a ...
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0answers
542 views
10
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4answers
2k views
Example reports for mixed-model analysis using lmer in biology, psychology and medicine?
As the general consensus seems to be to use mixed-models via lmer() in R instead of classical ANOVA (for the often cited reasons, like unbalanced designs, crossed ...
10
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2answers
1k views
What would a confidence interval around a predicted value from a mixed effects model mean?
I was looking at this page and noticed the methods for confidence intervals for lme and lmer in R. For those who don't know R, those are functions for generating mixed effects or multi-level models. ...
10
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1answer
123 views
Two years of data describing occurence of violence- testing association with number of patients on ward
I have two years of data which looks basically like this:
Date ___ Violence Y/N? _ Number of patients
1/1/2008 ____ 0 __________ 11
2/1/2008 ____ 0 _________ 11
3/1/2008 _____1 ...
10
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0answers
181 views
In a multi-level model, what are the practical implications of estimating versus not-estimating random effect correlation parameters?
In a multi-level model, what are the practical and interpretation-related implications of estimating versus not-estimating random effect correlation parameters? The practical reason for asking this ...
9
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3answers
6k views
How to interpret main effects when the interaction effect is not significant?
I ran a Generalized Linear Mixed Model in R and included an interaction effect between two predictors. The interaction was not significant, but the main effects (the two predictors) both were.
Now ...
9
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2answers
4k views
Multiple comparisons on a mixed effects model
I am trying to analyse some data using a mixed effect model. The data I collected represents the weight of some young animals of different genotype over time.
I am using the approach proposed here:
...
9
votes
1answer
4k views
Unbalanced mixed effect ANOVA for repeated measures
I have data from patients treated with 2 different kinds of treatments during surgery.
I need to analyze its effect on heart rate.
The heart rate measurement is taken every 15 minutes.
Given that ...
9
votes
1answer
214 views
Is it allowed to include time as a predictor in mixed models?
I always believed that time should not be used as a predictor in regressions (incl. gam's) because, then, one would simply "describe" the trend itself. If the aim of a study is to find environmental ...
9
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2answers
3k views
How can one do an MCMC hypothesis test on a mixed effect regression model with random slopes?
The library languageR provides a method (pvals.fnc) to do MCMC significance testing of the fixed effects in a mixed effect regression model fit using lmer. However, pvals.fnc gives an error when the ...
9
votes
1answer
465 views
Why does bootstrapping the residuals from a mixed effects model yield anti-conservative confidence intervals?
I typically deal with data where multiple individuals are each measured multiple times in each of 2 or more conditions. I have recently been playing with mixed effects modelling to evaluate evidence ...
9
votes
2answers
192 views
What model for a challenging data set? (hundreds of time series with a lot of nesting)
I have quite a complicated data set to analyze, and I cant find a good solution for it.
Here is the thing:
1. the raw data is essentially insect song recordings. Each song is made of several ...
8
votes
6answers
5k views
Significant effect in lme4 mixed model
I use lme4 in R to fit the mixed model
lmer(value~status+(1|experiment)))
where value is continuous, status and experiment are factors, and I get
...
8
votes
1answer
5k views
How to interpret variance and correlation of random effects in a mixed-effects model?
I hope you all don't mind this question, but I need help interpreting output for a linear mixed effects model output I've been trying to learn to do in R. I am new to longitudinal data analysis and ...
8
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1answer
263 views
Can slopes in linear regressions be used as the independent or dependent variables in other regression models?
I have 100 patients and each patient have 10 longitudinal serum creatinine measurements. The estimated glomerular filtration rates (eGFR) were calculated from a MDRD formula comprising gender, age and ...
8
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1answer
228 views
What are the different types of codings available for categorical variables (in R) and when would you use them?
If you fit a linear model or a mixed model there are different types of codings available to transform a categorical or nominal varibale into a number of variables for which paramaters are estimated, ...
8
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1answer
158 views
What to do with heterogeneity of variance when spread decreases with larger fitted values
I am trying to produce a linear mixed model the R code is as follows.
lme(Average.payoff~Game+Type+Others.Type+Game:Type+Game:Others.Type+Type:Others.Type,random=~1|Subjects,method="REML", ...
7
votes
1answer
2k views
What is the difference between generalized estimating equations and GLMM?
I'm running a GEE on 3-level unbalanced data, using a logit link. How does this differ (in terms of the conclusions I can draw and the meaning of the coefficients) from a GLM with mixed effects ...
7
votes
2answers
357 views
When should I *not* permit a fixed effect to vary across levels of a random effect in a mixed effects model?
Given a predicted variable (P), a random effect (R) and a fixed effect (F), one could fit two* mixed effects models (lme4 syntax):
...
7
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3answers
265 views
Concepts behind fixed/random effects models
Can someone help me to understand fixed/random effect models? You may either explain in your own way if you have digested these concepts or direct me to the resource (book, notes, website) with ...
7
votes
2answers
2k views
Questions about how random effects are specified in lmer
I recently measured how the meaning of a new word is acquired over repeated exposures (practice: day 1 to day 10) by measuring ERPs (EEGs) when the word was viewed in different contexts. I also ...
7
votes
2answers
6k views
Repeated measures ANOVA with lme in R for two within-subject factors
I'm trying to use lme from the nlme package to replicate results from aov for repeated ...
7
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3answers
3k views
What is the difference between using aov() and lme() in analyzing a longitudinal dataset?
Can anyone tell me the difference between using aov() and lme() for analyzing longitudinal data and how to interpret results ...
7
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1answer
168 views
Can I fit a mixed model with subjects that only have 1 observation?
I have a very large dataset where I have repeated measurements over time for individual locations. Some locations might have 10 data points and some locations have only 1 data point. I fit a mixed ...
7
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2answers
3k views
Paired, repeated-measures ANOVA or a mixed model?
I have been asked to analyse some data from a clinical trial looking a two methods of measuring blood pressure. I have data from 50 subjects, each with between 2 and 57 measures using each method.
...
