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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Help! Generalised linear mixed model for repeated-measures crossover design in R

I am new to R and linear mixed model analysis. I have data I previously analysed using a three-way repeated measures ANOVA for a cross-over design study; however, as data points are non-independent, I ...
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Mixed models for longitudinal data

I'm starting to study the Linear Mixed Models (LMM) and the Generalized Mixed Models (GLMM) and I got kinda confused. If I want to apply logistic regression to a longitudinal data, I need to add ...
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Bayesian model comparison vs Bayesian Model criticism

What is the difference between Bayesian model comparison vs Bayesian model criticism? Can someone explain with an example?
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Model selection for Mixed Effects Regression - Correcting heteroscedasticity

My experiment consist on measuring the root mean squared error (RMSE) between a path and what the participant produces. To produce the trace each participant experiences 3 feedbacks (1st factor - ...
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34 views

Filling missing data points with lmer prediction model

I'm trying to interpolate the missing data point using lmer model prediction. Subsetting to a table without any na to the missing column of interest: ...
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45 views

Ways of modeling the same variable as both a time-invariant and time-varying predictor

This question has been asked and not answered before here. I am building a model attempting to predict heroin use over time in patients based on their use of amphetamine-type substances (ATS). ATS ...
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Mean-center continuous predictors for GLMMs?

I have a dataset with a non-negative, right-skewed response variable and at least one non-negative, right-skewed predictor. Given the non-Gaussian, non-negative distribution of the predictor variable, ...
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51 views

Interpreting random effects in zero-inflated models

For context, I have a longitudinal study measuring counts of bacterial sequences in human stool collected during a dietary intervention. Initially, I was going model the change in each bacterium (...
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57 views

Obtaining valid win probabilities from contest data using a binomial model

I conducted an enclosure experiment on lizards where I recorded contest outcome for every male-male combat. We had three morphs of lizards (o, w, y) in each enclosure. I am interested in obtaining ...
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How do I write a mixed-effect regression model (MRM)?

So I am trying to write a MRM with both random intercept and random slope. I know the general model is as follows, yij = b0 + b1xij + vi0 + vi1xij + eij However, I want to actually write my ...
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56 views

What type of statistical analysis to perform?

I have an experiment with 10 subjects. Each of them has to exert force and real-time feedback is received. Each subject experiences all 3 types of feedback (within-subject factor). Moreover, each ...
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22 views

Continuous outcome variable - Select between GEE and Linear Mixed Models

What are the arguments for and against selecting GEE and Linear Mixed Models when the outcome variable is continuous? Are they any circumstances where one performs better than other? The data I am ...
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Mixed model with panel data when some cases have constant responses (zero) over time

I have a panel data with about 300 units observed over a period of 4 weeks. In each week, I recorded a response that is a binary variable, y, for each unit of that week. For about 50% of the units, ...
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Can I use location as a random effect when treatment levels are not exactly the same across those locations?

I am working on a data set that aims to test various treatments with respect to vegetation regeneration. The experiment is replicated at many sites across a large geographical gradient and has been ...
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How to add a covariate in the linear mixed model

I'm creating my LMM including three factors (A,B,C) as fixed effect, and D as the random intercept. At the same time, I also want to include a covariate (E) to test whether the covariate influence the ...
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Binomial GLMM (GLMER) with proportions in unbalanced, observational panel data: nesting issues and errors

Thanks in advance for reading this long question. I am new to mixed models and having several doubts about a mixed model (lme4's glmer, binomial) with multiple levels, measuring a proportion (0,1) ...
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How do I interpret the posteriors in a skew-normal mixed model?

I ran in brms a model with "skew-normal" link function. I would like to know how to interpret the model output. All my independent variables are scaled. If it was a model with normal link function I ...
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How to test for differences with multiple observations per subject under the same (level-2) condition?

I'm trying test for the difference in a numeric outcome (WearTime) that was measured 7 times (7 consecutive days) for each subject under the same condition (Season) that was measured at the ...
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Why not all contrasts showing up? [duplicate]

I have a categorical variable with 3 levels: low, mid, and high. I want to do all-pair comparisons with the following contrasts: ...
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Random Effects or Fixed Effects? Help! [closed]

I hope you can help me! Within the limits of my bachelor thesis, I will have to estimate either, a fixed effects- or a random effects model using Spotify Streaming Data. Basically, my dependent ...
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Assessing variability in a repeated measures study

I want to assess technical variability/dispersion between several same-subject measurements (i.e which groups have more variability): My data consists of a set of cases (with age and sex variables) ...
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lme4 - which option is the right one? [closed]

Let's say I have an experiment with 5 examinations done at 5 time points (t1..t5), when the subjects are assessed for some continuous variable, say, DV. I want to analyze their change from baseline (...
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How to analyze repeated-measures between-subject data using R?

I have to analyze data from an study with following design: I measure the subjects' response to a series of stimuli on a 4-level Likert-scale. Each subjects sees 10 different stimuli, but they are the ...
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Interpretation of between subject factors from a Mixed Models Anova with non-significant within factor effect

I just received results from a 91(Electrode-Combinations) x 2(Groups) x 2(Condition) mixed model ANOVA design, where Condition is the the within-subject factor or more precisely the repeated measures ...
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Can I do model selection comparing model computed using aov and lmer?

I am interested in model selection and wonder if it is appropriate to compare an anova (generated using aov) to a linear mixed model (generated using lmer) using AIC?
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Mixed Model Equations

In this paper on page 1924 it is stated that \begin{equation} var(u \mid y) = \sigma^2[G - GZ'H^{-1}ZG] \end{equation} can be written as \begin{equation} var(u \mid y) = \sigma^2[G - (Z'R^{-1}Z + ...
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Does this allow conclusions about an interaction in a linear mixed model?

I am analysing an experiment where groups received either one type of verum treatment (there are two different types of verum treatment) or a placebo treatment. I want to find out whether the ...
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Hausmann test for Fixed vs Random Effects Models

I run a fixed and random effects model with the same variables and got similar results. The Hausmann test indicated (=1) that I should use the Random Effects Model. However, when I added a lag ...
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Likelihood of linear mixed effects model

Consider the following model $$\left \{ \begin{array}{l} y_i = x_i\beta + z_ib + \varepsilon_i,\\\\ b_i \sim \mathcal N(0, \Sigma), \quad \varepsilon_i \sim \mathcal N(0, \sigma^2), \end{array} \right....
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Importance of absolute values of the covariance matrix in the nonlinear mixed models

I am fitting a nonlinear mixed model (three-parameter logistic function) without any hierarchical structure. I have adopted an unstructured variance-covariance structure for the random effects. Is it ...
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Mixed Effects Model Using Censored Data

I am attempting to analyze left-censored hormone data collected in a repeated measures design, and am having some difficulty employing an appropriate method to account for the censored nature of the ...
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64 views

Fitting a Linear Mixed Effects Model

Suppose I have data on 4 units, $X_i(t_{ij})$, for $i= 1,2,3,4$ and $j = 1,\dots,10$. That is, I have 10 observations for each unit. The observations for unit $i$ were recorded at times $t_{i,1}, \...
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Predictive performance of joint models versus standard survival models

I am trying to show that predictions based on repeated measures of markers (using joint modelling of repeated markers and time to event models: JMbayes package) are better than those based on only one ...
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How many levels within a factor is too many for an ANOVA?

I am running a mixed model with three factors. It is labeled as a strip-split design. The vertical level is A, the horizontal level is B, the splits come from factor C (plant varieties). This is ...
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Mixed-effects modelling of mortality rates

I have a dataset with annual observations (1990-2016) on neonatal mortality rates (dependent variable) for countries 1, 2, 3, 4, 5, and 6. The independent variables are indicators 1, 2, 3, 4, and 5. ...
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Implementing a truncated regression for a normal distribution in R

I'm not a statistician but I'm working with some experimental psychology data. I have a distribution of responses on a -4 to 4 scale. Usually, these type of variables is treated as continuous. I have ...
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Joint models with time to progression

Consider a RCT (Randomized Controlled Trial) which aims at assessing the efficacy of a drug in patients suffering from a given cancer. In this trial, $p$ individuals are observed at several time ...
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Model for Panel data with correlated time-invariant variables

after days of reading, I start to get a feeling about the different assumptions, tradeoffs and such for different models. But I still can't find the right answer. I asked a question about the choice ...
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What are the conclusions to be drawn when a t-test is significant but a linear mixed effects model is not?

I have 30 participants. They have a pre score and a post score. I am testing whether this changes. There are five observations per participant. When the data are analyzed using a t-test there is a ...
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R: LMM with covariate

I know there have been a number of posts on lmer, but I am struggling to find my answer through research and am hoping to get your help. I am analyzing data from a study with the following data: 1) ...
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Take paired data into account in lmer mixed model

I would like some help with setting up a linear mixed model with paired data. I have a dataset where each participant is tested twice: either with a manipulation or without a manipulation. There are ...
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Does it make sense to see if success of one thing determines the success of another

I have modeled whether a bird is detected by an antenna (1=yes, 0=no) with the following predictor variables: length of visit, species, and site. Individual ID is a random effect. I am not also ...
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Grouping by subplot in mixed-effects model

I have a strip-split experiment: Vertical = TrtA, 2 levels Horizontal = TrtB, 5 levels Subplots = Trt C, 20 levels I know how I would usually run this, but there are so many levels of treatment C ...
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R coxph vs. coxme: Vastly different Coefficients of Determination

Comparing comparably defined models in R's coxph() and coxme() I experienced hugely different results when calculation the Coefficient of Determination using MuMIns r.squaredLR. For the coxme()-fit ...
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Mixed effect nested anova

I try to find a good model to my data but I get stuck all the time as I'm not so good at statistics. I have data on approximately 100 fishes and each fish has been incubated in one of four possible ...
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How are PQL, REML, ML, Laplace, Gauss-Hermite related to each other?

While learning about the Generalized Linear Mixed Models, I often see the above terms. Sometimes it seems to me these are separate methods of estimation of (fixed? random? both?) effects, but when I ...
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Should I use a GEE model for a mixed logistic regression problem with a multinomial outcome?

I'm trying to model linguistic data where my hypothesis assumes that a multinomial categorical response from a subject is a function of fixed effects (gender and subject's occupation, say) and, since ...
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Addressing spatially nested data in nMDS?

I have an experiment comparing bird community composition in different forest stands, having subsampled each stand a few times. Is there any way to account for this subsampling (i.e., non-independent ...
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Choice of model/strategy for multiple regression analysis

I am doing an econometrics course where I am to do a regression analysis on some firm data. I want to analyze some shipping data of frozen goods to predict the temperature of the shipped goods at ...
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39 views

Calculating sums of squares for mixed-model ANOVA

I'm trying to get an understanding of how to calculate the sums of squares values in a mixed-model ANOVA (mathematically, not just the syntax for R or SPSS!). I've been trying to figure this out for a ...