"Mixed effects models" refers to models that have both fixed effects and random effects. They are used to model longitudinal data or data that are clustered & thus do not have independent errors.

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Negative binomial mixed effect model for repeated measures with R - prediction and plotting

I have a dataset to analyze in which a response was recorded at the ends of months 1,3,4,5,6 in 187 patients. All patients had the responses recorded in each week, and all patients started a treatment ...
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Nesting v. interaction in LMM

I have a continuous response variable, a continuous predictor (P1) and a variable (elevation, P2) that could be treated either as continuous or categorical (I guess?). I also have an ID as the random ...
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mixed effect model design with a sampling variable

I am trying to specify a formula for a linear mixed effect model (with lme4) for my experimental design, but I'm not sure I'm doing it right. the design: basically ...
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Hypothesis testing: If not a p-value in mixed effect models, then what?

I've been working on a messy, repeated measures data set of endocrine data looking at a small group of variables (after eliminating several uninteresting contenders in exploratory data analysis), each ...
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45 views

Large differences between raw (plotted) data and least-squares means from mixed model

I’m analysing data with mixed-models (using the afex package which I believe is based on lme4) from an experiment that had a ...
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How to model time-series data with nested random and fixed effects?

I'm analysing PAM fluorescence data from an experimental set-up that I duplicated from an earlier experiment with a missing control. That's why I haven't given the statistics of the experiment much ...
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Post Hoc Analysis in Mixed linear models

I tested whether different version-styles of a loading screen (hourglass vs. progress bar) in different progression patterns (linear, accelerate, decelerate, irregular, binary) affect time estimations ...
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43 views

Pooled OLS, fixed, random or mixed effects?

I am analysing a simple balanced panel data with the following variables: ...
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R lmerTest and Tests of Multiple Random Effects

I'm curious about how lmerTest package in R, specifically the "rand" function, handles tests of random effects. Consider the example from the lmerTest pdf on CRAN that uses the built in "carrots" ...
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82 views

Examining trends with interactions and with stratification - obtaining discordant results

I'm examining the effect of income (categorized into quintiles) on a response variable during different years (from 2003 to 2014). I adjust for some other covariates and have repeated measurements on ...
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23 views

Treatment of mixed effect models for Box-Cox transformation

To analyse the Box-Cox transformation in a mixed effect model, no simple transformation/ code in R exists. So which of the following approaches would be valid ways and why? 1) Take a random sample ...
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How do I fit a linear mixed model in R with autocorrelation, when the effect of time is of no interest?

I am attempting to fit a linear mixed model with the lme function using R. My data involve repeated measures, but the effect of time is not of interest to me, so I don't want to include it as a fixed ...
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34 views

Material difference between Mixed Effects Model and normal Linear Model

I have a question about normal linear models vs mixed models. Say I'm predicting prices for certain products, and I know two things: store and brand: In a linear model (lm), this would be: ...
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Is there a more efficient way to partition my data for use in lme4?

I'm currently using lme4 to fit the following model: Model = lmer(CA ~ P + T + S + (1 | Study), Data) P and T refer to pressure and temperature, and there is an ...
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Study on both hands of patients, mixed effects?

We want to test the correlation of a certain surgical procedure on the hand (carpal tunnel) and the development of trigger digit. We have both hands of the patients, some hands underwent surgery, ...
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34 views

Striping in residuals for linear mixed effect models

I am looking at the effects role has an opportunities to collaborate between groups in a social network. At a basic level the data are modeled as: relRatio~role ...
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21 views

What does the dfbeta mean for an lmer regression?

According to the documentation: DFBETAS (standardized difference of the beta) is a measure that standardizes the absolute difference in parameter estimates between a (mixed effects) regression ...
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23 views

Heavy-tailed errors in mixed-effects model

I'm relatively new to statistical modelling and `R', so please let me know If I should provide any further information/plots. I did originally post this question here, but unfortunately have not ...
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26 views

In the optimal model, do I need to change 'REML=FALSE' to 'REML=TRUE'?

I did the model comparison using these three models: ...
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How do I identify a particular residual from a mixed-effects model in R?

Here's a plot of my residuals from a mixed-effects model in R (using lme4). There's one 'outlying' residual with a value of around 35 (index circa 90) that seems anomalous. I don't know if it has ...
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Random variable in mixed-effect model (ecological studie)

I'm beginner with the mixed-effects model, so I already apologize if my question is a bit naive. My problem is the following : I sample each time 30 plants in 6 populations on 9 mountains. So I ...
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65 views

Should I include this fixed effect? lme4 likelihood ratio test and lmerTest anova disagree

I have a mixed-effects model with two fixed effects and one random effect (group membership) estimated using lme4. log_dv ~ iv1 + iv2 + (1 | group) I want to ...
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1answer
25 views

power for mixed-effects model

I wonder if there is a simple way of calculating an achieved power for a mixed-effects model. The fixed effects are the intercept and a slope. The random effect is for the intercept at the two levels ...
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Which is the difference between conventional 2-way repeated measures ANOVA and mixed effect ANOVA?

Assuming I have two within-subjects factors (Xw1 and Xw2) for my experimental design I can therefore perform two way repeated measures ANOVA using the conventional procedure in R ...
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Real motivation for using mixed effect models, and when to use them and when not to

My question might sound naïve, but despite my internet search, I wasn't able to find a satisfactory answer. I've been introduced to linear regression, linear fixed effect and linear mixed effect ...
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1answer
35 views

What is the nature of the normality assumption in models for longitudinal data?

I'm working on a longitudinal dataset to which I've been fitting non-linear mixed effects model in R. Regarding normality, I have a few questions: Can I assume that a longitudinal data is normally ...
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26 views

Mixed-effects model without the random effect in the design?

Is it appropriate to create a mixed-effects model (for example, using SAS Proc Mixed) that specifies a random effect but does not include the random effect in the model itself? I ask because it seems ...
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Intercept in random effects mixed model no longer significant

When I add a categorical fixed effect to my mixed model (with one random effect and three continuous fixed effects) the intercept is no longer statistically significant. Does this mean that the newly ...
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442 views

Obtaining adjusted (predicted) proportions with lme4 - using the glmer-function

I aim to estimate the annual proportion of patients (% of patients) that are smokers in a population whose age and sex must be taken into account. In other words, I want to calculate the adjusted ...
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1answer
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Why are the beta values provided in lmer() different than simple group means of observations?

In a 2-level mixed-effect model, the equation for level-1 is $$Y_{ij} = \beta_{0j} + r_{ij}$$ where $\beta_{0j}$ is the mean outcome for the $j$-th group. I ran the following model: ...
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107 views

R-Metafor: Meta-analysis and mixed effect model

This is an example of my dataset ...
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69 views

Post-tests to consider in mixed models

I have a mixed model of the form y~condition + Replicate + Error(Replicate) but at the moment, and am running into difficulties in performing a post-hoc test. I ...
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Mixed effect linear model R

Could someone please help me with interpretation of the results I've got using nlme package from R. I have 3 groups of animals, each group is divided into 3 subgroups, and each subgroup has a number ...
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What happens when fixed and random effects overlap?

For example, if your response is the number of ticks on deer, and you sample deer at 10 sites. You include 'site' as a random effect, but you also want to include the density of trees at each site as ...
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How to analyse the ratio of two continuous variables sampled repeatedly over time

I am measuring reproductive hormones in dolphins over time to look at seasonal changes. The sample type (respiratory vapour) that I am using suffers from variable water dilution that cannot easily be ...
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Calculate elasticities of mixed logit

How do we calculate the dis-aggregate direct elasticity of a random-coefficient logit model?
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79 views

Interpreting Reaction Time data with mixed-effects model

I have a problem with interpreting Reaction Time results with mixed-effect models. In the experiment, participants were split into 2 conditions. They looked at the same set of pictures and then took ...
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glmer in R: Significance estimates are not robust to order of data frame

I'm using a mixed effects model with logistic link function (using lme4 version 1.1-7 in R). However, I noticed that the estimates of significance for fixed effects change depending on the order of ...
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Where is the correlation parameter in the linear mixed-effect model equation?

Moscatelli et al provide the equation behind generalized linear mixed-effect models, and their paper is available online: http://www.journalofvision.org/content/12/11/26.long They say: "We ...
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Specification of Mixed Model

I have very big experiment with 70 places around country. In each place there are several experimental plots where measures have been done. There were several measurement occasions during last 50 ...
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1answer
53 views

Are level 1 and level 2 residuals in a mixed effects model always normally distributed?

Take this mixed effects model: $y_{ij} = \beta_0 + \beta_1X_{ij} + \mu_{j} + \epsilon_{ij}$ The level 2 residuals are $\mu_{j}$ and the level 1 residuals are $\epsilon_{ij}$. As I understand the ...
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Linear mixed effects model methodology suggestions

4 beehives were equipped with sensors that collected temp, humidity, pressure, decibels inside the hive. these are the response variables. the treatment was wifi exposure, the experimental groups ...
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Averaging against mixed-effect model

I have experimental data that contains information about 50 participants who performed a task in five different conditions (different set sizes). The result is the time spent on the task. My data is ...
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Mixed effects model with level 2 explanatory variable

Take this linear mixed effects model, which is discussed on the CMM website: Centre for Multilevel Modelling $y_{ij} = \beta_0 + \beta_1X_{ij} + \beta_2\bar{X}_j + u_j + e_{ij}$ The variable $X$ is ...
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Recommendation for books/notes for linear mixed effect models for longitudinal data?

I'm a beginner in data analysis who needs to learn (say in a period of 2 to 3 weeks or so) the key ideas and techniques in the linear mixed effect models for longitudinal data. I'll apply them in ...
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Not sure whether to include random effect that's related to fixed effects

I'm unsure about whether I need to include a random effect in a mixed effects model that I'm running, as the fixed effects are related to this random effect. I'm looking at how the intelligibility ...
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Can any one give me inf how I can form X, Z, R, G, and A matrices using dummy variables using the posted info below?

Y=Xb +Zu + e, where y represents a vector of observed (measured) phenotype values, b is vector of unknown parameters for “fixed" effects, while X is corresponding design matrix, u is vector of ...
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1answer
150 views

Probabilities of odds ratios in random intercept models?

I'm using R and the lme4 package to compute mixed effects models with binary outcome (glmer). I have included continuous ...
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38 views

Mixed effects models - which are the random parts?

I have data on family care for elderly people. Data stem from 6 EU counries. People were asked at baseline and followed-up one year later. Now I'd like to find predictors that explain why people ...