"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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Model failed to converge

I'm doing a variable selection for the interaction gender:type2 now ...
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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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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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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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31 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 ...
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72 views

Multilevel analysis in R and Stata

I am trying to replicate a multilevel logistic analysis which uses a dyadic time series data set and R. As for my part, I am using the same data set but Stata. The original syntax has the following ...
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interpreting an interaction of two continuous variables in a mixed effects model [duplicate]

I am hoping for some guidance on how to interpret the interaction in a mixed effects model. The interaction is between two continuous variables (EarlyLanguageExposure and NeighborhoodSize). My ...
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1answer
51 views

Coding of categorical random effects in R: int vs factor

I have a problem with coding of a 2-level categorical predictor variable in R, and subsequently using it as a random slope in lmer(). I can keep the factor as numeric, coded using the treatment ...
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33 views

How to report mixed effects logistic regression

I have several models predicting different binary outcomes as a function of time (binary variable: before/after intervention) and age (ranges 4 to 14), measured in different students within different ...
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Proc Mixed for a random slopes model - contrast the slopes?

I have a need to make predictions about a set of students $^1$ who are nested under teachers, under schools, under districts. I have produced the below model, and I now wish to do some forecasting at ...
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68 views

Using the same variable as a fixed and random effect in Mixed Effect Models

The experiment this data comes from an experiment where two people collaborate to put objects in a specific order. The Direction has the target array on their screen, and the Matcher has a scrambled ...
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1answer
89 views

Interpreting a linear mixed effect model's interaction term

I am a biologist and am attempting to analyze the effects of time and location on depth. I was told I needed to use a mixed effects model to account for the random variables of Individual and tracking ...
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40 views

Trying to understand the basics of a mixed-effects logistic regression model for a 10-step continuum

I am trying understand how to correctly build a mixed-effects logistic regression model in R. I believe my model is pretty simple and straight forward but I'm lacking in experience and uncertain I'm ...
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49 views

Fixed effect vs random effect when all possibilities are included in a mixed effects model

In a mixed effects model the recommendation is to use a fixed effect to estimate a parameter if all possible levels are included (e.g., both males and females). It is further recommended to use a ...
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Mixed effects structure: Main effects in random slopes with between-subjects design

My question is about whether it is appropriate to include certain random slopes in a mixed effects model with a between-subjects design. This is my first question on this stack exchange, and I'm ...
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One observation per level in mixed-effect model

Field explains how to analyse repeated-measures data using linear mixed-effect models (LME). See Field et al., Discovering Statistics Using R, 2012, p. 573. However, the way he specifies the model, ...
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how to fit nlmer non-linear mixed model and have asymptote fixed?

I'm trying to compare the model where asymptote value varies over subject and the one that does not. I've fit the first (the one that varies) but can't seem to figure out the latter. The first one is ...
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What statistical test is performed by summary(glht(model, linfct=mcp(factor=“Tukey”)), test=adjusted(type=“none”))?

I have data that I have fit using lme with the following structure (Subject is implemented as a random effect in order to account for multiple paired comparisons): ...
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Compare linear mixed models with Likelihood ratio tests and significant fixed effects

I am comparing two models with likelihood ratio tests and I have found the -2LL increases with the more complex model (when a 3-way interaction between 3 fixed effects is included). However, the tests ...
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How can I model this problem?

Genetic algorithms are a kind of evolutive approach to problem solving where solutions are randomly generated and crossed with each other as to produce other solutions. With each generation or ...
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Adding a variance structure when fitting a gamm with Gamma distribution

I am using the code below to fit a gamma GAMM introducing a variance structure that informs the model that variance of the response variable is much larger in one of the levels of the factor coast ...
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1answer
112 views

F stats for post hoc test of a linear mixed effects model

I have an unbalanced linear mixed effects model with three fixed factors of various levels and one random factor for my repeated measures data (for details see here). Thanks to your help I managed to ...
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Measurements from two raters. Should I use multilevel/“random-effects” model?

I have several variables that were measured on patients, for most patients the variables of interest were measured by 2 independent "raters". Most of the variables are binary. I need to compute the ...
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Accounting for heteroskedasticity in lme linear mixed model?

I have a data set where I measured the number of molecules (M) present in cells as a function of drug (with or without) and days of treatment (5 timepoints). I repeated the experiment 3 times, with ...
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time varying continuous covariate with one single binary outcome

Despite having only a single binary outcome for each ID, there are multiple correlated measurements for the same test for each ID at different timepoints. The individual ID´s are obviously ...
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How trustworthy are the confidence intervals for lmer objects through effects package?

Effects package provides a very fast and convenient way for plotting linear mixed effect model results obtained through lme4 ...
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Two repeated measures treatment analysis. Regression of the delta or mixed effect model?

We want to study the effect of a certain treatment on performance on a test and I would like to have some suggestion from you. We want to use a regression model in order to control for confounders. ...
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Comparing between random effects structures in a linear mixed-effects model

During a recently asked question about linear mixed-effects models I was told that one should not compare between models with different random effects structures using likelihood ratio tests. Up until ...
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73 views

Mixed and random effect model with multiple crossed random effects in lme4 vs nlme

I am trying to fit a few models as follows for my data of observations recorded from $p$ genotypes planted in $n$ locations for $m$ years. The aim is to estimate BLUPs finally. $$Y_{ijk} = \mu + G_i ...
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2answers
94 views

How to report a linear mixed-effects model equation

I have run a linear mixed-effects model, with one fixed effect (dd) and a random slope and intercept term for individual (fInd) and would like to know how to report the results? In particular, I would ...
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Joint Models vs the 'usual' time-dependent Cox regression for time-varying predictors

I've got a methodological question, and no data set attached. Suppose I aim to fit a proportional hazards model (Cox) for survival data. I have multiple observations for each individual (data in long ...
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1answer
78 views

Testing whether random effects are normally distributed in R

I've been working on a GLMM in R and I see that an assumption of the test is that the random factor must be normally distributed (that is, unless you're using a package like ...
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REML or ML to compare two mixed effects models with differing fixed effects, but with the same random effect?

Background: Note: My dataset and r-code are included below text I wish to use AIC to compare two mixed effects models generated using the lme4 package in R. Each model has one fixed effect and one ...
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Using a mixed effects regression model for between-subject design?

I have data from a between-subject experiment, where every subject was assigned to one of the two conditions, and completed varying number of trials (as much as they wanted). Number of trials is ...
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Using glmer, why is my random effect zero?

We’ve run a mixed effects logistic regression using the following syntax; ...
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The biological significance of ANOVA 3-way interaction

Dear statistics experts, I have trouble to find a sensible statistical approach to back up some very obvious (at least to my eyes) interpretation of a dataset (see descriptive plot below). I measure ...
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Aligned Rank Transform with random factor

In an aligned rank transform preceding a two-way ANOVA, the procedure is: save residuals by performing a standard ANOVA use Aggregate to determine effects for group means (mij for interaction, ai ...
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lme() with several within and between (categorical and continuous) subject factors

I am currently trying to analyse data from an experiment of mine and I have done some searching for instructions on the usage of the lme() function for R, since I am looking to analyse my data with a ...
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2answers
209 views

Interpreting the random effect in a mixed-effect model

I am looking at several dependant variables for which I created LMMs of the following kind: DV ~ Group + (1|Subject) + (1|Time) Now I am struggling with how to ...
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Reporting Fixed Effects as (partial) correlations?

I'm doing a linear mixed effects analysis in which I'm really only interested in one of the fixed effects. I have several other fixed effects and a random intercept term, but none of them are ...
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Random effect with zero SD in LMM

In my mixed-effects model there are one fixed effect and two random effects (subject and time of measurement). fit <- lmer(DV ~ group + (1|subject) + (1|time)) ...