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Questions tagged [mixed-model]

Mixed (aka multilevel or hierarchical) models are linear models that include both fixed effects and random effects. They are used to model longitudinal or nested data.

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Random effect or not?

My intent is to model plant growth with a generalised linear mixed model. Let's say I sampled growth of 10 plants each on 10 plots in five different (non-consecutive) years. In order to find out which ...
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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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anova and summry, inconsistent results

I am fitting a linear mixed effect models with two factors (mPair with 6 levels, and spd_des with 3 levels) and their interaction, using "sum" contrasts. The summary of the fit and an anova (using ...
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treatment and sum contrasts, inconsistent results

I am fitting a linear mixed effect models with two factors (mPair with 6 levels, and spd_des with 3 levels) and their ...
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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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Model building, how to include information on data point quality?

I have a dataset with count data predictors and a marker on their reliability or completeness. With 2 options: 0 - Data is not confirmed (could be higher); 1 - data is confirmed to be complete. The ...
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linear pattern in residual vs fitted

My question is about addressing linear relationships between model residuals and the response variable. I am using a linear mixed model to model the relationships between two response variables (...
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Random effect vs. fixed effect with a huge amount of dummies

I am interested in examining inventor features on their inventive performance using patent data. I have an unbalanced panel data of 7000 inventor-year observations on 3000 inventors over 15 years ...
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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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R glmer.nb : how building model with interaction between categorial variables

Before posting this, I made some research but I am very struggle with my modelling approach, so I will try to be clear in what I want to do with my data. I want to apologize if my questions are close ...
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Interpretation very small standardized coefficient beta

In one of my studies I have results similar to the below: β=-0.0007 (95% CI: -0.0009, -0.0002), p=0.01 Since β is so small (but also the Confidence Interval (CI)), is this result still meaningful? ...
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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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Longitudinal data: RM multilevel model vs. mixed ANOVA

My longitudinal data consists of yearly fund-level ESG ratings (environment, social and governance criteria; relative measure between 0 and 100) of 5000+ institutional investors over 10 years. These ...
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Covariance matrix for the random effect in mixed effects model

According to this post, matrix Omega and sigma are in the results of lmer when we fitting ...
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How does d-prime calculation relate to binomial mixed models with probit link?

for a study I tested participants in a same-different task (1AFC) about melodies. There were 3 versions of each melody (within-subjects factor "version"). So d-prime seems the natural response/...
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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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how to understand random factor and fixed factor interaction?

Let's say I fit this model to the Oats data set lmer(yield ~ Variety + (1|Block/Variety), data=Oats) ...
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order of levels in crossed design

How can I determine if a factor A is nested in B or B is nested in ...
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estimate of variance-covariance matrix for linear models with correlated observations

For linear models $$y_{n \times1}=X_{n \times p}\beta_{p \times 1}+\epsilon_{n \times 1}, \text{ where }\epsilon \sim N(0,V)$$ If in a real life problem we have data as $(y_1,x_1),(y_2,x_2),...,(y_n,...
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Centering in longitudinal linear mixed modeling - center by participant mean, timepoint mean, or participant by time grand mean?

EDIT: I was incorrectly looking to center my outcome variables. Only center predictors, and decide on group mean or grand mean centering by how you want to interpret your intercept. I have 150 ...
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t-test/regression - how to account for random effects? [closed]

I need your help on how best to test the following hypotheses in R. Each observation in my data has RaterID and RaterGender, ...
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My ASReml GLMM is predicting “NA” values for one of my variables, any suggestions on how to fix this? [closed]

My question is: What is the relationship between malaria and schistosomiasis? Therefor, I have plotted this GLMM; ...
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1answer
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Interpretation of intercept only random effects models

I am estimating the global risk of infection risk in a population of patients, but these patients are clustered in hospitals and wards/departments. If I just take the crude prevalence (infected ...
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1answer
31 views

Mixed model - maximum number of groups?

I am trying to fit a mixed model to determine the effect of X on Y after controlling for non-independence in my data. Non-...
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Test statistics of LMM with significant covariate interaction

When reporting on the LMM that I fitted to my data with R, I was asked to include the test statistics (df and others). But I have no idea where to extract them from, I don't see them in the summary as ...
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Interpreting significant model parameters in less well fitting AIC model

I have two linear mixed effects models (among other models representing competing hypotheses) as coded in R: ...
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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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Can I use a mixed model even when my independent variables are all fixed effects?

I need to use longitudinal data for my model. Two possible options to deal with the lack of independence between observations: GEE and Mixed models. But, how Mixed model can even be an option if all ...
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singular fit in lmer, despite no high correlations of random effects

I ran a mixed effects model a few weeks ago, it all went fine, no errors. Here is the model: ...
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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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Estimation of the baseline hazard in a generalized linear mixed-effects model (Poisson)

I need an estimation of the baseline hazard in a semi-parametric survival random effect model. Initially, I tried to do it with splines and the frailypack package. ...
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Integrated mixed model testing correlation and difference in correlation across factors

I'm currently performing the following analysis : Computing $r_j(Y_{ij}, X_{ij})$ for each design cell (factor with level 1 or 0 for each unit) Estimating effect of factor on $r(Y,X)$ with a linear ...
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1answer
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Why is my Mixed Effects Model (LME) results different from my repeated measures ANCOVA (AOV) results?

I have been trying to compare the effect of a treatment over time, controlling for a continuous covariate. So two groups (treatment vs control) are given different treatments and compared pre and post....
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How to isolate the effect of dichotomous predictor?

I want to isolate gender differences in preferences for a particular attribute of a product based on data available about their product purchases. I understand that I have to use a mixed Poisson ...
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Price elasticity vs Discount Elasticity

I have a case where I do not have many regular prices, but I have many discounts (different kind) which last a different number of days. Is there something like discount elasticity and how to adjust ...
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Am I employing and interpreting linear mixed-effects modelling correctly here?

I'm interested in the effect of a categorical variable X (let's say the application of heat) on continuous variable Y (the expression level of a particular gene). I have measurements of Y for samples ...
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How can I test whether two logistic regression coefficients are identical in mixed models?

Similar to question here. 3 variables (1 continuous (X) and 2 categorical (A & B)) predict 1 dichotomous variable in generalized linear mixed models. Both variables A and B are dichotomous and ...
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Linear mixed models: how to interpret 3-way interaction if there is also repeated measures?

I performed a linear mixed models on a data set that measured 'outcome' for 4 groups of individuals at 8 different time points. In summary, the data set is built up of 3 fixed factors: Factor 1: ...
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How to fit a longitudinal GAM mixed model (GAMM)

I have repeated measurements of individuals, like this ...
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Why does model converge when factors are releveled?

I am building a mixed effects logistic regression to predict linguistic (corpus) data. I have coded for various factors, some of which do not correspond to a large amount of data. For example, one ...
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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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warning: Some predictor variables are on very different scales: consider rescaling

I am using multilevel modeling in lme4 package in R. With the warning of rescaling variables, how can I find out WHICH variables need rescaling? All variables are centered. Dummy variables are coded ...
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Post hoc for random effects in mixed effects modelling

Can we carry out a post hoc test like (Tukey, using mult-comp) for "glmer" models for the random effects? My response variable is binomial and there are three levels in the random effect variable. ...
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Why p-values are not significant even though AIC values improved a lot in model selection using GAM mix modelling and beta regression

Dear StatExchange community, I am studying disease progression in plant leaves and I am trying to estimate differences between a wild-type and a mutant plant. To achieve this I am using the ...
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using `lmer` to fit the linear mixed effects models

Edit: I know some people vote this question is off-topic since it is more like a Cross Validated question. However, I am not here to ask about the coding thing (but I might word in the wrong way). I ...
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Linear Mixed Model for evaluation of students

My dataset about students (n=74) contains one outcome variable (exam points/integer) and eight predictor variables: 2 categorical: gender [F,M] study years [1,2,3] 6 continuous variables: age [...
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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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Mixed Model Repeated Measures for Before & After Comparison

I'm trying to assess the effectiveness of a program by comparing employee performance before the program vs. after the program. I have 4 years (2 years before vs. 2 years after) of individual-level ...
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Time series with continuous predictors and outcomes

I am trying to carry out a multivariate regression model where my main predictor is a continuous variable that changes over time, and my dependent variable is also a continuous variable that changes ...
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1answer
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Point mass at zero and a chi square distribution with one degree of freedom

I am unclear about the critical value of a point mass at zero and a chi square distribution with one degree of freedom. How to find this?