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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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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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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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1answer
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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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45 views

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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What are the uses of panel data regression?

I have a dataset with Cross-section and Time-Series Data. After doing some reading I came accross a concept named as "Panel data analysis/regression". However, I am still not clear how and why we use "...
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172 views

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 ...
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36 views

With lme4, is it possible to weight group-level random effects by similarity?

I'm creating a model with two group-level random effects: district (factor) and age (factor) and a response, ...
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53 views

Wilcoxon Test with Random Effect

I would like to test if there is a significant difference in the speed of movement between 2 treatments for different females. For each female, I have several sampling points. I have a table with the ...
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1answer
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Estimates radically change when including Random Slopes in Multiple Logistic Regression

I am examining the fixed effects of two within-subject experimental manipulations (i.e., Ambiguity 0 = No / 1 = Yes, and Uncertainty 0 = No / 1 = Yes) on a dichotomized variable (i.e., Punishment, 0 ...
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1answer
64 views

Mixed logit random parameters for individual specific variables

It is my understanding that in a mixed logit model there can be two types of variables, alternative specific and individual specific. For example, in a dataset for choices of fishing modes like this (...
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1answer
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Compare using `lme4` and `nlme` for mixed effects models

Sorry it might be a more Stack Overflow question but I was reading this nice cheat sheet for using function lmer in package lme4 ...
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1answer
49 views

How to include covariates in a nested model?

I am new to multilevel model and having trouble understanding how to include covariates. In my mode, I have Industry and Country ...
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1answer
104 views

Interpreting BLUPs or VarCorr estimates in mixed models?

I am referring to the question. When estimating random effect (RE) variance or correlation, the estimations are different in VarCorr(mod) function and when ...
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GAMM with multiple and crossed random effects

I am new to Generalized additive mixed models (GAMM) and I'm trying to model a behavioral response variable (time spent shading eggs by a nesting bird in minutes ...
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1answer
82 views

How to fit a longitudinal GAM mixed model (GAMM)

I have repeated measurements of individuals, like this ...
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29 views

3 Level Hierarchical Models in STATA; Null model fails to converge

3 Level Hierarchical Models in STATA; Null model failed to converge About the Dataset I am working with DHS (Demographic and Health Survey Data) data. DHS uses a two-stage cluster sampling process. ...
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1answer
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Are anxiety measure fixed or random factors in this scenario?

As a psychologist and not a statistician, I have always used ANOVAs to perform analyses on repeated-measures designs but have since learned you should instead use mixed linear modeling with these type ...
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1answer
31 views

Crossed or nested random effects?

I've conducted an experiment in which 20 pairs of talkers are conversing in their first and second language (L1 and L2, respectively) both in quiet and in noise in a fully crossed design: L1 in quiet ...
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Random effects vs Rubin's rule to obtain pooled parameter estimates from multiply imputed datasets

I would appreciate any help to understand the statistical difference between using random effects and Rubin's rule to obtain pooled parameter estimates from multiply imputed datasets. For example, if ...
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Treatment (equivalent to experimental groups) in Experiment as Fixed AND Random Effect in Mixed Model Linear Regression

I have data from a sociology experiment with three groups. Each group is equivalent with a different treatment for a subject (n=700). The treatment were surveys, differing in the amount of information ...
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1answer
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Formula for cross-classified (a.k.a., crossed random factors) mixed effects model with interaction between two “second level” variables

I have a crossed-classified (Hox, 2010) mixed effects model—also known as crossed random factors (West, Welch, & Galecki, 2015), but I am struggling with how to write the formula for an ...
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Minimum sample size per cluster in a random effect model

Is there a rational for the number of observations per cluster in a random effect model? I have a sample size of 1,500 with 700 clusters modeled as exchangeable random effect. I have the option to ...
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R Mixed-Effect Models for 2-way Repeated Measures Design with more than 2-levels in each factor

Background: I am running an experiment with the following parameters. Design: 2-way Repeated Measures Design (as of right now there are NO between-group/grouping variables Dependent Variable: A ...
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1answer
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weird assumption of one-way random effects ANOVA

$$Y_{ij} = μ \, +\, A_i \, +\,ε_{ij}$$ In Ch5 (random effects one-way ANOVA) of my textbook, it mentioned that $A_i$ (see the model above) is assumed to be $\sim N( 0, \text{constant_variance} )$ ...
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GLMM - Aleatory effects in R [closed]

I have a question if you could help me? I studied during 2 days (48 hours), 8 times per day (every 3 hours), 3 nests per species (2 species), the number of ants every 3 min that walk by a point. I ...
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1answer
61 views

Random effect in GAM - what are the smooth functions used?

In the GAM package in R created by Simon Wood there is a selection of the smooth function basis. I sort of understand the options such as bs='tp', bs='cr', etc. But bs='re' seems odd... that does ...
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34 views

Simulating survival meta-analysis data (with a random effect) [closed]

I would like to simulate survival meta-analysis in clinical trials on R but I'm not pretty sure of what would be the best way to do it and what would be fitting more the reality. The data would ...
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1answer
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A few questions about the calculations behind the metabin function, part of the R 'meta' package for meta analysis of binomial data

I am new to meta analysis, and am reading about how to perform meta analysis with binomial data. I'm looking for some clarification on some of the results given by the metabin function, which is part ...
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1answer
31 views

Does a panel regression model make sense for my data?

This might be a bit of a newbish question, but I recently picked up a forecasting project at my job, and I'm trying to figure out whether it makes sense to run a panel regression like a Fixed Effects ...
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How can I plot fixed and random effect in a boxplot?

In case a random effect has influence on the weight of outcome variable how would I plot the corrected values? I'm not sure if "variables getting weighted by the random effect" is something that is ...