# Tagged Questions

Refers to a class of models developed to account for correlation that may occur within nested data.

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### 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 ...
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### 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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### 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 ...
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### Computing repeatability of effects from an lmer model

I just came across this paper, which describes how to compute the repeatability (a.k.a. reliability, a.k.a. intraclass correlation) of a measurement via mixed effects modelling. The R code would be: ...
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### 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 ...
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### 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 ...
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### 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: ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### Residual diagnostics in MCMC -based regression models

I've recently embarked on fitting regression mixed models in the Bayesian framework, using a MCMC algorithm (function MCMCglmm in R actually). I believe I have understood how to diagnose convergence ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### Mixed model vs. Pooling Standard Errors for Multi-site Studies - Why is a Mixed Model So Much More Efficient?

I've got a data set consisting of a series of "broken stick" monthly case counts from a handful of sites. I'm trying to get a single summary estimate from two different techniques: Technique 1: Fit a ...
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### Difference between generalized linear models & generalized linear mixed models in SPSS

I am wondering what the differences are in SPSS between analyze-> generalized linear models-> generalized linear models & ...
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### Multiple comparisons on a mixed effects model

I am trying to analyse some data using a mixed effect model. The data I collected represent the weight of some young animals of different genotype over time. I am using the approach proposed here: ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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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### 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 ...
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### 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 ...
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### 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. ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 ...
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### Advice on explaining heterogeneity / heteroscedasticty

I am looking for any help, advice or tips in how to explain heterogeneity / heteroscedasticity to biologists in my department. In particular I want to explain why its important to look for it and deal ...
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### Is this an acceptable way to analyse mixed effect models with lme4 in R?

I have an unbalanced repeated measures data set to analyse, and I've read that the way most statistical packages handle this with ANOVA (i.e. type III sum of squares) is wrong. Therefore, I would like ...