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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Multilevel model for education data, if individuals within cluster change (school) between time points

If I am wanting to fit a multilevel model across two time points and the first time point is Primary (uk education system, age 7-11 - keystage 2) but the second time point is secondary education (uk - ...
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How to run a mixed ordinal logistic model with one random effect term when the random effect has only 2 levels

I am trying to run a mixed ordinal logistic model and I have already tried to use the clmm function, but my random effect only has two levels. I get the error message: Error in getREterms(frames = ...
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Cox PH controlling for multiple events

I'm working on a cox proportional hazard analysis in R using the survival package. I´m analysing covariate effects on fish movement within a study area. The study area is divided into two zones ("...
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question of a Poisson random effect model

Assume a Poisson random effect model (with a random intercept) $$\log E(Y_{it}|b_i,x_i)=\beta_0+\beta_1x_i+b_i$$ $$b_i \sim N(0,\tau^2)$$ How to derive the population-averaged effect of one unit ...
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Can causal relationships be inferred from a random effects panel model?

Can a causal relationship between two variables be inferred from a random effects panel model? I estimated the following one-way random effects (RE) panel model: $\mathrm{Gini}_{it} = \alpha + \beta \...
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Fixed effect model selection when some candidate models have singular fits

I have an experiment on the performance of a new animal management technology. The response is a proportion and I have three continuous input variables. There is one grouping factor of interest (...
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How do you interpret Beta coefficients for Fixed Effects Panel Data Models?

Let's say we have House Prices across different cities (Bristol, Brighton, London, Glasgow) across time (Monthly data from 2016-2020) and we're trying to predict it using unemployment and crime. t = ...
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Random effect with compound symmetric covariance structure in glmmTMB

I have a dataset of abundance of a kind of rodents(AA) in 63 sites, and want to know which environmental factors can explain the rodent abundance, and because the sampling sites are basically locate ...
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Linear mixed effects modeling with MZ and DZ twin pairs

I have a question on how to deal with following experimental setup. I have data on microbiome and metabolomics for twins that are either MZ or DZ, and thus we have only pairs in the dataset. I ...
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Investigating the existence of plasticity (random intercept model vs. random slope model) in a response variable that is not normally distributed

I wanted to explore if the change in speed between day and night is similar among a set of individuals. To me, the logic way of testing this hypothesis is running a random intercept model and a random ...
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Why is there heteroskedasticity even though no relationship seems present in the residual plot?

I estimated a random effects panel model and performed the Breusch-Pagan (BP) test for heteroskedasticity. The test is significant, meaning that there is heteroskedasticity. However, the residual plot ...
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Understanding the dependencies between random effect values in lmers

I have two related (basic) questions. Linear Mixed Effects models (as implemented for example with the lmer package in R) are hierarchical. I assume that this comes from the assumption that random ...
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Random Effect in twin study of both MZ and DZ twin pairs

I am a bit stuck with the use of linear mixed models and its random effects in a twin study analysis. What I have is microbiome data for twins that are from MZ twin pairs and DZ twin pairs, so no ...
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How to deal with crossed and nested factors at the same time in a linear mixed model?

I've recently started analysing the data for a project using linear mixed models but am not sure how to deal with crossed and nested factors at the same time. In my study, each participant reported ...
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Can I improve linear model coefficient estimates using group information without working it into model?

I am fitting a linear model in order to predict future observations. The training data consists of about 1000 observations. Each observation comes from one of 10 individuals, which means I have about ...
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How is the standard deviation of random effects estimated?

For example, the sd of the random intercept reported by lme4 when I use lmer or glmer is much higher than if I just calculated the sd on the list of intercepts generated from ...
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Using restricted maximum likelihood on marginal residuals

In a mixed-model setting, I want to estimate the variance components and the pertaining random effects of a random-intercept/random-slope model. The coefficients of the fixed effects have already been ...
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Help with Modeling Random Effects Model Interaction

I am having some trouble determining the correct modeling strategy for my research. I have a sample of approximately 500 movie observations nested within approximately 250 franchises. The average ...
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Centering in Multilevel/ Mixed Modeling (MLM/HLM) Cross-Level Interaction Small Groups Dichotomous Variable

I am having some trouble with the literature on centering in multilevel models. I cannot seem to find a clear answer for my unique situation. I have a multilevel model with approximately 500 level 1 ...
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How to handle rank deficiency in a generalized linear model?

I am trying to understand if my model is sound even if there is rank deficiency. I am performing a generalized linear model with a binomial (or binary) distribution. My model has the fixed effect of ...
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Is there a way to correct for degrees of freedom when using a generalized linear model with a Poisson distribution featuring random effects?

I am running a generalized linear mixed effect model with a Poisson distribution to analyse count data. The model has a random effect that takes into account multiple observation obtained by the same ...
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What to do when removing a perfectly correlated random slope and intercept stops model from converging?

Occasionally I will build a linear mixed-effects model with random item and subject slopes and intercepts. I'm speaking generally here because it is a general problem. The model will converge, but ...
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How to simulate data of a random intercept effect model in R?

I want to simulate data of the following random intercept effect model in R $$Y_{ij}=\alpha+\beta x_{ij}+u_{0,i}+\epsilon_{ij}$$ $$u_{0,i} \sim N(0,\tau^2)$$ $$\epsilon_{ij} \sim N(0,\sigma^2)$$ Here ...
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multilevel logistic regression via maximum likelihood in R

I want to develop a mixed effect logistic regression in R using likelihood function and compare the results (estimated parameters) with the output of glmer function. I couldn't find a good material ...
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Nested random effects for testing individual choices when choices are made in a group

I'm planning an experiment where individuals' choices will be measured. I want to test individuals' choices before and after an intervention. The problem is the individuals are in groups and cannot be ...
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Mixed effects model: nesting when having a maximum of 2 cases per multiple nests?

Hello everyone and thank you in advanced for your willingness to help: it's been years since I've been reading and learning from this community. I hope to get some light with my question. I have 50 ...
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Design effect of a random intercept model-how variance and effective sample size are calculated

I am reading about the random intercept model for the two-level analysis. The effective sample size is defined as neff=Ntotal/(1+(n-1)*ICC), where 1+(n-1)*ICC is also called the design effect. I ...
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Which mixed model is closest to GLS with unstructured covariance? Random intercept + slopes or random slopes only?

I would like to closely reproduce a model fit via generalized least square method with unstructured residual covariance by using a mixed model. Which mixed model is closest to GLS with unstructured ...
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How to create a B-spline basis without intercept and linear trend included?

I want to fit the following model using splines: \begin{align} Y(t) = \beta_0 + \beta_1t + \sum_{j=2}^{d} \beta_jB(t)_j \end{align} where $B_j$ are the basis functions. However, when I run the ...
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Does linear mixed-effects models have an advantage for specifically cross-over effects?

I have not read this anywhere but what I think is mixed models have some advantages (against other methods such as ANOVA) for cross-over effects since they treat individuals differences (intercepts) ...
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How do I fit a nonlinear mixed effects model with multiple observations from the same sample units using nlmer()?

I am trying to fit a nonlinear mixed-effects model with lme4. However, I am not sure how to adequately account for my sampling design. The model is supposed to ...
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What are some uncontroversial examples where random slopes are appropriate for a binomial logistic regression model?

I'm trying to wrap my head around when you would use random slopes in GLMs. Specifically, I'm having a hard time imagining a situation where you'd use random slopes for a binomial logistic regression ...
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How do I check for statistically significant differences between averages generated by a random effects model?

I have several average procedure success rate data points along with population sizes for three different procedures from multiple studies. I pooled the average success rate data points in inverse ...
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Degrees of Freedom for Variances in SAS Proc MIXED

Below is a SAS proc Mixed code generated by JMP. Both JMP and SAS give me a confidence interval for the variance components (in the table "covariance parameter estimates"). I would like the ...
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Adding study site as a random effect drastically changes the model - what does that mean?

I apologize for asking what is surely a common question. I am analyzing my own data, and am unsure what a random effect is doing to my results. I will describe a simplistic version of my study design: ...
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Linear mixed models Models

I would like to comment on the estimation of the random effect with REML and without REML. This was my comment: "The variation between chicks for the model with REML is 545.70 and the variation ...
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Would i do a mixed model MANOVA, a one factor MANOVA followed by individual MANOVAs?

Ive been trying to learn about MANOVAs and cannot seem to find examples relatable to my data, or I am not understanding the language being used to teach the concepts. I have stable isotope data which ...
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Strange residuals vs. fitted values plot for linear mixed model / hierarchical model

I have read a couple of related questions and their answers, but nothing really fits to my specific case. I have a model like this: ...
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How to interpret linear mixed effects model for non-changing binary fixed effect?

Let's assume we have a model looking at the effect of gender (m/f) on test scores (0-100). Data is being pulled from multiple students across multiple universities, with the restriction that a student ...
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Should both "Student ID" and "Quiz" be random effects in a mixed effects model?

I'd like some help constructing my model, please. Research question: Does the rate of homework completion affect student quiz scores. My data is at the student-chapter level. This means I have chapter-...
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Clarification on linear mixed models grouping and process of parameter estimation

I'm having difficulty in conceptualizing what is happening between linear effects models. I'm looking at the idea through the notion of different level models all coming together would form a ...
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Model for repeated time-series data?

I have multiple time-series data measuring the same response over time for one subject. It is the same experiment that is replicated multiple times to get a more robust estimation... I am interested ...
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Fixed/Random Individual (site-specific) Effect, Fixed/Random Time Effect - Panel Data

I am wondering if the following conclusions are true: fixed individual effects (location-specific fixed effects), do not allow for location-specific variation, but they do allow for time-specific ...
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How to scale data for nested random effects

Linear mixed-effects models are sensitive to scaling. Say that I have data on the performance of the students with multiple schools and classes nested in schools, i.e. in R lme4 formula notation ...
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How are random intercepts model fit?

I'm looking for the pseudocode of fitting a random intercept model but haven't found it. Can you explain what is the procedure used to fit a random intercept model? I'd like to know how each parameter'...
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Random effects tobit if random effects are non-normal distributed

I have the following (panel tobit) data-generating process: $y_{i, t}^* = a + bx_{i,t} + u_{i} + e_{i,t}$ $y_{i,t} = y_{i, t}^*$ if $y_{i, t}^* \geq 0$ and $y_{i,t} = 0$ otherwise. where $i = 1,..., N;...
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DF of multivariate multilevel random effects model

my question is concerning a multivariate multilevel random effects design. I have one between-subjects variable, gender. My outcome variable is composed of several (...
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Results from a Hausman Test

If the results I get from running a Hausman test in STATA is Prob > chi2 = 0.4504 does this mean I should use a FE or a RE?
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Panel Data- FE vs RE

I am trying to understand the different Panel Data models and I am getting confused by the different terms that people use, i.e., Random effect models and Random effects estimators and Fixed effect ...
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hierarchical linear model with moderation in R

Could someone please check if my model fit is correct??? Thank you!!!!!! Here is the background: participants fill out one baseline survey and seven identical follow-up surveys during a week. I have a ...
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