Questions tagged [random-effects-model]

Parameters associated with the particular levels of a covariate are sometimes called the “effects” of the levels. If the levels that are observed represent a random sample from the set of all possible levels we call these effects "random".

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11 views

Prove variance of composite error in Random Effects model [closed]

need some help on proving the variance in a RE model. See question below: I'd like help with Q(ii) if possible. Thank you. My teacher said the equation (14.10) is not needed for proving the variance, ...
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R lmer4 package multilevel model adding random effect with 0 notation

I do not understand what the difference between these two models is ( I am using the lmer4 package) ...
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Constraining all variances to be equal in multiple random intercepts linear models

Let the mixed model formulation be the following: outcome ~ fixed effects + (1|A) + (1|B) + (1|C) A,B and C are binary covariates. Is there a way in R (either in ...
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Feasibility of Linear Mixed Effects Models (aka. MLM) after Unflattering Visual Inspection

Is it still of utility to run a full-blown LME modelling procedure when the visual inspections between the predictors and outcome variable are characterless? I have been arguing that it makes little ...
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Ramifications of small + unbalanced group sizes, small number of groups for fixed & random effects models?

I have a variable (call it 'group') that I would like to treat as a random effect in a logistic regression. However, the number of groups is small (9 groups, larger than the recommended absolute ...
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Understanding how to tell whether random effects assumption is sufficiently violated to pose a problem in practice

Consider a situation where I want to predict a binary health outcome for patients with various medical conditions, who are treated at different hospitals. I want to use patients' medical conditions as ...
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A correct mixed model for longitudinal data

This is a rather basic question and there are many similar questions here on CV. However, I could not find answers to my specific three questions below. My apologies, if I may have overseen something. ...
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How to generate data with prespecified autocorrelation and random crosscorrelation in a growth model?

I would like to simulate data from an unconditional growth model with one fixed (level 2) covariate $x_{i}$, cross-correlation $\rho_c$ and autocorrelation $\rho_a$. The model should have a random ...
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nesting vs not nesting?

I am following the tutorial from Bodo Winter. Bodo created the following model on page 10: ...
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Interpreting nested random effects

I was playing around with some data and had hard time to understand the meaning of nested effects. Here's an example of a dataset (selfesteem2 from package datarium)...
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Bivariate random effect problems in selection models (Mixture Cure model)

I am currently working on a mixed effects selection model. The selection model is a logistic model with a Gaussian random effect. The principal model is a survival model with a Gaussian random effect (...
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Do I gain any information from removing the random intercept model?

I am fitting a mixed effect model to data from a behavioural task where each participant performed the task multiple times, trying to predict a binomial response, something like the formula below: ...
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ordinal logistic regression random effects and specify correlation structure

I am dealing with an unbalanced repeated measure dataset. My outcome variable, y, is a 3 level ordinal variable : Hot, Moderate, Cold. My independent variable is a repeated time varying measure. Due ...
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Model fit is improved ONLY by random effects in linear mixed effects model

I am trying to evaluate fixed effects by model comparison using lme4. Every time I add fixed effect, I also add corresponding random intercept and slope. When I compare a model with fixed effects (m1) ...
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Should a within-subjects variable be modeled with a random intercept and slope even if within-subjects correlations are minimal?

I am evaluating an analysis of an experiment in which each participant was shown 5 pairs of stimuli which represented options that participants could choose between - call the two options in each pair ...
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Write-up for lme model with multiple random factors

I have an lme() model with 2 random factors. I have significant results for one fixed factor and am writing up the results. However, I cannot seem to find how you can write up such results to include ...
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Interaction between fixed and random factors in mixed model

I am running an experiment with 3 different factors arranged in a factorial arrangement 3x3x3 (randomized complete block design with 4 blocks). These experimental plots are also replicated spatially ...
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Mathematical notation of a mixed effect model with different variance structures

I am assessing the relationship between a response variable (Y) and a predictor (X) using repeated measures in 6 individuals (...
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GLMM for unbalanced design, nested random factor or fixed factor?

The Goal Determine if the abundance of ectos differ between sites. The set up The data is percent abundance of ectomycorrhizal fungi from soil samples. There are ten soil samples per plot and there ...
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Algebraic notation of my longitudinal mixed effects model

I have fit two models in R using the NLME package. The first one includes time varying variables and the second one time invariant variables. Model 1: Y ~ Time_measured, random = ~ Time_Measured|ID ...
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Choice between static and dynamic panel regression

I have a panel dataset with countries as individuals observed per year. My analysis concerns a macroeconomic study and as often happens in these cases (I would not be wrong but they are commonly ...
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Poisson distribution complications with proportions, GLMM

In order to analyse which factors have greater weight in the proportion of incidence (number of infected inidivuals against total individuals) difference within different habitats a Generalized linear ...
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Using a standard OLS linear regression or a panel model for small sample size

I have created a dataset involving certain NLP variables for news-websites over time. The data involves six news-websites which are observed over 27 time periods with some missing data. As I only have ...
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What should be the minimum observation size per group in a random effect [duplicate]

I searched on SO and CV for a minimum sample size per group for a random effect in a mixed-effects model but failed to find relevant answers. Some say there should be the minimum of 6 groups to be ...
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Mixed-effects log-linear regression for counts -

I've read other answers but couldn't find exactly what I was looking. I have generated the following contingency table from my data: ...
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Deriving the standard errors for ML estimator of random effects

Consider the random intercept model with one covariate: $$ y_{ij} = \beta_0 + \beta_1 x_{ij} + u_j + \epsilon_{ij} $$ where $u_j \sim N(0,\sigma^2_u)$ and $\epsilon \sim N(0,\sigma^2_\epsilon)$ ...
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Interpreting the statistical model implied by an lmer formula for mixed effect modelling

Consider the scenario in which a dataset has two grouping variables (say group 1 and group 2), and a time variable $x$. I would like to understand the difference between the following two models: <...
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What are the steps to simulate data for a linear model with random slopes and random intercepts

I have searched this site for existing answers but so far I didn't find anything. I did see this one How to simulate a random slope model Unfortunately it doesn't answer my question. I would like to ...
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How to interpret random effect coefficients in glmer

I am studing relationship between the competition facing a hospital and the death at 30 days within it. I performed mixed-effect model assuming that patient in same hospital should be more correlated....
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Mixed model with random slope but no random intercept?

I have two questions: Is it ok/when might it be ok to specify a mixed model with a random slope but no random intercept? How would one specify such a model in lme4/glmmTMB? I am working on a dateset ...
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Group centering for interactions with within-between mixed panel model

I need to update a model to incorporate an interaction between a time-invariant categorical variable and a demeaned time-variant variable. I'm unsure about how to correctly use group-mean centering ...
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How to fit the right mixed model?

I want to look for a relashionship between the competition facing a hospital and mortality within the hospital. Assuming that patients in the same hospital may be more correlated than patients in ...
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How to estimate panel data where not all variables are correlated with the individual specific effect?

For an assignment in my masters course microeconometrics I am working with panel data. I need to model log(wage) with gender, race, number of weeks worked in a year, experience, years of education, ...
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Multiple Membership vs Crossed Random Effects

I see that there is a multiple-membership tag, but I can't find a good explanation of what a multiple membership model is, or how to go about fitting one. In my limited understanding, it seem very ...
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Linear mixed models for repeated weight measurements with random slopes: no model will correctly predict negative slopes

I have a dateset with 120 subjects with associated weights, captured for at least 20 days during a treatment. I wanted to use the weight on the first day (weight_0), the blood pressure and the main ...
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Lmer model syntax for a combination of crossed and nested random effects

I'm trying to use the lmer() function in R to specify a particular random effects structure for a model that has four levels: each measurement on a students occurs ...
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Alternative to panel data regression for testing covariates

I have a balanced panel data set containing variable y = daily numbers of COVID-19 reported cases at the municipal level over a 3-month period. I want to know if another daily-measured variable (x) is ...
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fixed effects vs random effects vs random intercept model

This might sound a repetitive question but after reading many articles and posts online, I could never understand it entirely. I read somewhere that a random intercept model is a type of random effect ...
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Is it a must to include a random slope in a mixed model?

I am learning about fitting mixed models and I find when it is justified to include or exclude a random slope rather confusing. Some tutorials suggest that although the maximal random structure should ...
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Which ICC estimator to use under the fixed effects model?

In the random effects model $$y_{ij} = \mu + \alpha_j + x_{ij} + \epsilon_{ij}$$ the intra-class correlation coefficient is given by $$ICC = \frac{\sigma_{\alpha}}{\sigma_{\alpha}+\sigma_{\epsilon}}$$ ...
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Linear mixed models: reference about effect sizes debate

I have heard many times over that there is "ample debate" about whether or not effect sizes (and also p-values) for linear mixed models should be computed and how they should be computed. Is ...
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Issues with random effects: what to do when analyzing sites with all 0's or all 1's?

I'm analyzing data that looks at the survival of artificial bird nests under different treatments. These nests were grouped across 80 sites, with 6 nests per site. I have created a binomial model on R ...
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Crossed or nested random effects in a repeated measures and a between-subject design?

After reading a lot of material on nested and crossed effects, I am still unsure on whether the random effects in my design are nested or crossed. I would really appreciate advice from some more ...
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Nested and crossed effects in 3-way interaction in lmer

I am running a mixed model in lmer, testing the effects of Covid restrictions on sleep, comparing 2 cohorts of individuals- one from 2019 and one from 2020, coded 0/1 (between subjects). Each ...
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Estimating the random effect structure and variance-covariance matrix for RRs from observational studies

long time reader, first time poster. Have found this community to be extremely helpful but alas have not had luck finding a previous question relating to this: I am attempting to run a meta-regression ...
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Using random effects to adjust for cluster-level confounding?

There is a usage of random intercepts to adjust for unobserved cluster-level confounding, as for example argued here: Are random effects confounding variables? How do random effects adjust for ...
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How to interpret VarCor output when the random slope is an interaction?

Context: I am running a binomial mixed-effect model with a logit link function. My response variable is a proportion of response (success/failure). As fixed effect I have ...
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Parsimonious Mixed Models

I recently read a paper on the trimming of random effect structure by Bates, Kliegle, Vasishth and Baayen (2015). My understanding is that the Parsimonious Mixed Model they proposed mainly follows the ...
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Regarding modelling longitudinal variables using Two stage mixed effects modeling

I have a question about the basic understating of key statistical methodology. I came across the idea about two stage modelling to incorporate longitudinal predictors. Lets say there is a continuous ...
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LRT comparing a random effects model and nested logistic regression model

I have a logistic regression model of the structure y ~ x1 + x2, and a generalized linear mixed model (GLMM) with random intercept and random slope, of the ...

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