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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Adjust for correlation within group in linear mixed models

I'm trying to use a linear mixed model for this experimental setup: Students are tested three times, before and after a lecture, and after a pause, at two occasions. I want to test whether age and ...
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heteroscedasticity in a linear mixed model of longitudinal data

I want to evaluate the effectiveness of a psychological intervention in a RCT. My study consists of 150 subjects. Half of them were assigned to the intervention group. They are nested within three ...
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Replicate Stata 'variance' and 'robust' in R for mixed effects methods [closed]

I am working with a small dataset of clustered data. The experiment is on mice, testing the efficacy of a substance for neurons cells within mice, and delivery of a fatty acid substance between mice. ...
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23 views

Multiple comparison adjustment with multiple outcomes, measured over time

I am trying to work out the most appropriate way to adjust for multiple comparisons. I have 20 biomarkers which have been measured at 4 timepoints (baseline & three unevenly spaced follow-ups). I ...
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Satterthwaite degrees of freedom for Linear mixed models

Suppose, I have a mixed model of the form; $Y = X\beta + Zb + \epsilon$ Where $b\sim N(0,D)$ with $D$ being the unknown random effects covariance matrix and $\epsilon\sim N(0,\sigma^2I)$ with $I$ ...
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Mixed-effect logistic regression with very large dataset

I am conducting linguistic research to determine whether a property of the subject (animacy) of a sentence has its effect on whether a particular kind of preposition phrase will be mentioned. I ...
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15 views

ICC and power for mixed models

I'm simulating data for a mixed model in order to estimate the needed power for a study. I have 3 groups, a control group and two treatment groups. The effect sizes for the two treatment groups are 0....
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1answer
25 views

Hypothesis test of two population means with correlated observations

I'd like to run an A/B experiment where my outcome measures are conversion rate, and mean spend. I'd like to use two proportion Z-test and z-test of two population means, however many users in the ...
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30 views

Testing contrasts in multilevel models

I'm trying to think of a way to test certain hypotheses regarding an experiment I've run. It's a 2 x 3 x 4 within-subjects, repeated-measures design. I would like to fit a (cross-classified) ...
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23 views

Panel data regression (R)- temperatures at weather stations correlated across time and across stations

I have a balanced panel dataset with a few dozen weather stations' hourly temperature readings across several decades. I have a measure of population density around the weather station over time as ...
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1answer
73 views

Quadratic terms in glmer

I'm looking for some references that explain step by step how to model logistic regression to longitudinal data (repeated measurements) in R. I know that I can use the ...
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1answer
34 views

Nested random intercept

I am calculating a three level HLM. The first level are the measurement points, the second are subjects and the third therapists. I am investigating the effect of an intervention, which is only ...
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1answer
25 views

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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29 views

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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66 views

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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1answer
46 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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1answer
47 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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1answer
24 views

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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61 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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72 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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76 views

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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58 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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1answer
24 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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32 views

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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64 views

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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1answer
25 views

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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1answer
42 views

Binomial GLMM (GLMER) with proportions in unbalanced, observational panel data: nesting issues and errors

Thanks in advance. 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] in three time periods. My data ...
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18 views

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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1answer
24 views

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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18 views

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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5 views

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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14 views

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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12 views

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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18 views

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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1answer
12 views

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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1answer
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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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28 views

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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26 views

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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1answer
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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63 views

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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47 views

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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1answer
43 views

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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1answer
18 views

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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2answers
43 views

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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1answer
21 views

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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36 views

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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1answer
23 views

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) ...