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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Modeling repeated measure effect with linear mixed effect models (lmer) in R

this is the first time I'm posting a question here, I hope someone will read it soon :) I have the following problem: I have three groups of people (ADHD patients, ADHD patients under medication, ...
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Is is possible to estimate a mixed logit model with only individual specific parameters?

I am analyzing some data and I do not have any alternative specific variables in the dataset. The question is about the preference between taxi, uber and automated vehicle if all three have the same ...
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Variable selection for mixed models

Longtime lurker here. I have a question about determining informative variables in generalized linear mixed models (GLMMs). My background is ecology, and I primarily examine habitat selection under ...
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Interpreting Durbin–Wu–Hausman test with large sample size

I'm trying to determine whether to use random-effects or fixed-effects. The Durbin–Wu–Hausman is significant which suggests that fixed-effects are more appropriate. However, looking at the details, ...
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zeroed random effects after fitting a mixed effect model [closed]

I am fitting a linear mixed effect model with two categorical factors: mPair with 6 levels, and spd_des with 3 levels. This is a ...
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Is it correct to treat a confounding variable as random with mixed modelling?

In a semi-controlled experiment, seeds were sown in about 20 boxes, associated with 3 types of soil. A few months later, the morphological characteristics of the shoots were measured. We would like to ...
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diagonal var-cov matrix for random slope in lme4

I am fitting a mixed effect model with a random slope on a factor with 6 levels using the function lmer(). ...
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Problem with Assumptions of Panel data with random effects

I am studying with a Panel data 316 of observations and 73 groups. First, when I examine the homoskedasticity issue, I got following results with df(72,243) by using Levene et al. Test: W0: 2.5 (Pr>F =...
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Random-effects-meta-analysis-simulation: zero-estimates for tau^2

I am working on simulating a random-effects-model for comparison of the DerSimonian-Laird-method vs. Hartung-Knapp-Sidik-Jonkman-method in R. To do so, I chose different combinations of mu (true ...
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Repeated measures/pseudoreplication - Comparing all samples against all other samples

I am currently analysing some data, and I am not confident that I am going about it in as statistically sound way. We are trying to determine whether our treatments affect the distance between two ...
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Beginners question on panel data/random model and variables depending on change to previous year

This might be a silly question, but... I have panel data including time variant variables (funding, number of investors and postsperday) as well as time invariant variables (city) that looks like ...
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What is the difference between random-effects models, multilevel models and hierarchical models?

In the Bayesian paradigm, I have found examples of models that could be called any of the following: random-effects models multilevel models hierarchical models. Each of these categories even has ...
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How to Determine typical rate of progression with haphazardly collected data?

We are studying various parameters in extant patient records. Some patients were tested once. Some patients many times. All at different ages. but all have the same disease. We would like to use the ...
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GLMM with Variable Selection and Non-Negativity Constraint

I am trying to run a fairly complex GLMM with random effects and smooths. There are about 10 of these independent variables. There is also another set of 1000 variables. From this set of 1000 ...
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random factos really significant?

I have some confusion about random factors inclusion or not. I've used the function glmer.nb of the library MASS to analyse the effects of two fixed factors (temperature: 2 levels and salinity:3 ...
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Hierachical Random Mixed effect sizes

When using a mixed effect model the rule of thumb seems to be that you need at least 5 levels to use a random factor . Is this still True when you have a hieachical model. i.e A - 4 level factor B - ...
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Interpreting very high conditional and very low marginal R^2 in linear mixed effect model [closed]

I've fit a linear random slope mixed effect model to some time series data from multiple participants. Here time is the fixed effect and participant is the random effect. I've received a very high ...
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nested random effects in mixed effect models across different levels, and associated DF

I would like to fit a mixed effect model to the following dataset, but I am having difficulties figuring out the best way to define the random effects. For each subjects (...
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How do you use panel data to isolate the relationship of interest for a particular individual within your panel?

I have a panel data set where Canadian provinces are the individuals. (I have annual data from 1997-2017). I am using a random effects model to see the impact of an explanatory variable $X_{it}$ on ...
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variance-covariance matrix with negative entries on mixed model fit

I am fitting a linear mixed effect model in R (function lme), and I get a Var-Cov matrix with negative entries (Log-Cholesky). This does not allow me to compute confidence intervals on the standard ...
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Is a specific mixed model within the class of models generated by lme4?

Given $i = 1, ..., n$ people, we measure a continuous response $y$, a group $g = 1, ..., G$ and a class $c = 1,2$. All members ...
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Is it possible to resolve collinearity between a categorical and a continuous variable using a random effects model?

This question is related to Multicollinearity between categorical and continuous variable. Consider a regression model x ~ y + z + ... + w with outcome x and ...
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Using random intercepts in a multilevel model as dependent variables in a linear model

I have a mixed model with 3 levels: individual, city, and state, and so I get random intercepts for both cities and states. I understand that since cities are nested in their state, their intercepts ...
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What is the most common number appearing at the units digit of the scores in NBA game?

In the lottery market of NBA, the boss will divide the numbers(0-9)to 5 groups: 0and5, 1and6, 2and7, 3and8, 4and9, and the five groups will be given the same odds. How and why does the host of the ...
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Random effect VS Pooled OLS

I am a second year MSc ACFN student at Addis Ababa University, Ethiopia. Now, I am conducting my research on the "effect of leverage on profitability and I use a panel data". When I was trying to ...
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Its my model a Mixed model?

I am running some analysis with mixed model with R. I get differents measures from differents persons (person as random effect), during this analysis and looking plots for each people vs measures I ...
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Under what conditions does it make sense to fit random intercepts for an interaction, but not the main effects?

I am aware that when specifying the random structure for one factor (B) nested within another factor (A), we can use: ...
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How to combine random effect and nested random effect with lme

I'm doing a mixed linear model. And I have subjects who have been select in 20 schools. So I want to take this to account. For this, I want to put a random intercept for the "SCHOOL" variable and a ...
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80 views

Random effects in GAM

I'm modelling some biological function, outcome, in patients over 8 hours. Over time, I measure two additional covariates x and ...
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Should I treat these variables as random? (ecology/recruitment question)

I'm working with recruitment data for caribou. There are 13 different herds, sampled over 20+ years, once per year. Some herds are sampled consistently, some only a few times over 20 years. I'm ...
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Are there extant deep learning analogs to random coefficient (aka mixed) models?

Random coef models, applied to longitudinal data, capture response heterogeneity by cross-sectional unit. I've got a longitudinal prediction problem, in which I know that some "features" (or ...
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Mixed models. Random slopes only, mean and group centering?

Are random intercepts a theoretical/practical prerequisite to random slopes? Why? I have a three level (rep measures) mixed model where I wouldn't expect lvl 3 variation in initial status of outcome ...
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Understanding nested random effects - why is an interaction between factors involved?

I have read this question and answers: Crossed vs nested random effects: how do they differ and how are they specified correctly in lme4? however, I am struggling to understand why, provided that ...
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Why do we do crossed vs. nested vs. other random effects?

Let's try a theoretical example. I am trying to predict the math scores of students within schools. I see three ways I can model this with random effects: (1) I can "nest" the random effects. My ...
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Simultaneous non-significant variance parameters but significant co-variance parameters mixed models/random effects

I specified a linear mixed model in SPSS: TNA_HRQOL is the DV TIME_0 is a rep measures factor (0,1,2) which I specified as a covariate TK_Name (doctors) is LVL3 subjects, TNA_Name (individuals) is ...
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Defining fixed effect and random effect in a model

I'm unconfident that whether my understanding on fixed effect and random effect is correct: Fixed effect= variable that make inferences about the specific levels. Random effect= variable that make ...
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random effect variance as pseudo-rsquared in GLMM

Suppose I have data on the abundance of a species across multiple sites that differ in some covariate of interest. Suppose that the logarithm of the abundance (logAbun) meets assumptions for linear ...
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SPSS mixed models - using classroom as an effect in the model

I'm looking at data from a health intervention study done in one middle school (16 classes/"clusters" at that school). Half assigned to control, half to intervention. Is this an appropriate way to ...
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If change is DV and Pretest is covariate, should random effects take the form of (1|subjects) or (Pretest|subjects)?

I have Change from Pretest to Posttest (gain, no_gain, decline) as the DV. Pretest and Group as covariates. This called for a multinomial regression ...
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Multilevel generalized linear model (MGLM) with rank dependant variable : Specification issues

I am currently trying to estimate a multilevel generalized linear model (MGLM) on rank data using clmm function from "ordinal" R package. My dependant variable is a ranking variable repeatidly ...
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Including Time Invariant Covariates in a Random Intercept Model

Let us say we have a random intercept model for $n$ individuals $$y_{i,t} = x_{i,t}'\beta + \alpha_i + \epsilon_{i,t} \hspace{35pt} i = 1,...,n$$ where $x_{i,t}'\beta$ is a set of time variant ...
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How to know whether a random effect or a cluster effect is necessary for a mixed effect logistic regression?

I have 8 variables in my model out of which I have a group which is definitely not a fixed effect. I tried checking the random effect on the basis of the log-likehood test and it seems significant. I ...
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In generalized mixed-effects model, after fixed effects and variance covariance matrix are fitted, how are empirical random effects calculated?

For example, I would like to fit a logistic mixed-effects model. This article fitting glmm talks about how to fit fixed effects as well as variance covariance matrix of random effects. Theoretically ...
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Family fixed/random effects cross section

What is the appropriate Stata command for a within family comparison in cross section dataset? Basically i hear a lot about such comparisons, siblings comparisons or within mother comparison…. Still i ...
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How to build a LME with nested random effects? A study with a very comlicated experimental design

I am trying to analyse the data on the climbing behaviour of flies. The design of the experiment was rather complicated, so I am currently struggling to build a propper LME model. The flies have ...
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What are some good examples of working through a multilevel model by hand?

I've been learning about multilevel models lately, and I understand the concept of shrinkage and partial pooling (I think), but I'm still confused to some extent on how partial pooling actually ...
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Random effects for a mixed multinomial logistic regression in R

I have a dataset in which individuals, each belonging to a particular group, repeatedly chose between multiple discrete outcomes. Something akin to: ...
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How to include survey weights into a random intercept model? [duplicate]

I'm trying to run a random intercept model in R on an adolescent dataset with >100 schools (the school being the intercept). The data include a survey weight value for each observation, however lme ...
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Mixed effects random forest (MERF) in Python: random slope or just intercept?

Does the MERF implementation in python allow for random slope effects? If so, how? I assume yes, and that it is achieved using the Z matrix. With a column of ones for the intercept and a column for ...
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Use of lagged dependent variable in panel data

Intro: I’m doing a statistical analysis of men doing 5k-runs. The point of the analysis is to determine, if finishing close to a woman has an effect on their runtime. The variables I have in my ...