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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Which is the best method to analyse binary data in mixed models?

I wonder if there are suggestions about which method do use to analyse this type of data. My idea is to use glmer, or is there a better option? ...
11 views

Linear mixed model in R for repeated measures with non-randomized groups that have baseline differences

I have a question about how to analyze the results of a study I conducted. The study occurred on a remote island with a very small, unique population and in children. In order to be minimally invasive,...
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When an analysis with random effects returns random effects with a perfect correlation, does this mean that it can only estimate one of them?

I have read the recommendation to perform dimension reduction on a random effects structure. I'm trying to get my head around exactly what this means. I assume it has to do with the fact that often a ...
57 views

LMM: Non-independence of observations sharing a single fixed-effect value

I am interested in the effect of monkey's stress levels on the pitch of their calls. Each stress measurement is associated with a bout of calling (that is, multiple calls), and in some cases I have ...
14 views

Reporting RESULTS of least square means as post-hoc test for linear mixed model- Best practice

Anybody have good example of how to report the results of a least square means result of a Linear mixed model?- I welcome any guidance on good practices to report this kind of result. I posted below ...
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How to run mixed effects models with lots of 0's

I have ecological data (transects as the unit) from inside marine reserves and matched control transects that I would like to test the difference across 18 separate response variables. These are 3 ...
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Incorporate continuous group level variable in a hierarchical model?

I aim to assess the effects of difficulty (continuous variable) and trial type (0/1) on whether a subject has been correct in a logistic regression model. However, I have also measured subjects ...
96 views

Is this a random or a fixed effect?

I have a question about one of the variables in my study and whether or not it should be considered a random effect. I'm conducting a study of my school's 24 general learning outcomes (or "skills".) ...
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How can I adress problems of heteroscedasticity in mixed model analysis?

I am analizing pupil size data using mixed model analysis in R. I use lme() from package nlme. However, I am encountering serious problems of heteroscedasticity and ...
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Path Model with (endogenous) Treatment - which model?

I have collected data on the intention to create a new business of my students. I measured it before the course (t1) and after it (t2). I have data on their absenteeism in class and the time they ...
25 views

Random effects for mutually inclusive grouping factors

I am trying to fit a model on a set of data (e.g. 10,000 observations with 20 explanatory variables). The observations belong to 30 groups, G1, G2, G3, ... G30, so I need to account for the grouping ...
49 views

Overfitting model or issue of categorical predictors?

Is it possible to overfit a model by virtue of having too many categorical variables? I have 3 categorical variables and my dependent measure is continuous (or a ratio I guess, I'm measuring ...
27 views

Regression with paired, repeated measures design

I have a large population of books. Each book is either a hardback or softback (thus hardback and softback books are paired with one another by title), and can fall into two categorical genres - ...
18 views

Interpreting interaction effects in Factorial design

I have factor1 with 2 levels fully crossed with factor2 (5 levels). Now samples are collected from same experimental units at 6 different times. Time is used as within-subject variable. When I run ...
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Test for the influence of a manipulation on multiple dependent measurements (order effects, multiple comparisons)

I have a dataset which looks like this: ...
56 views

Multiple Nested Random Effects affecting a Mixed Model

I have a quite complex psychophysiological data dependant of different nested data in a repeated measures experiment. The first nested structure comes from the data collection were there are several ...
33 views

Feasibility of running mixed-effects poisson/logistic regression with correlation structure such as AR(1), Toeplitz

I'm not aware of any R package that lets me use specify the covariance pattern model such as in the package nlme and run the mixed effects poisson/logistic ...
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Comparing models: which model to choose?

I'm new to mixed effects modeling, so I need help understanding when it's appropriate to choose a model. So far I've been incrementally building my modeling with main effects and then adding in the ...
70 views

GEE logit / Poisson versus mixed effects Poisson / logit

There's a way to do Poisson or logit mixed effects and Poisson or logit GEE in R. What's the difference between GEE and the mixed effects models for Poisson / logistic regression? I heard its the ...
33 views

What is the meaning of the beta for the interaction between continuous variables in a linear mixed-model?

If I create a mixed-effects linear regression model similar to the following (using the lme4 package in R), where all of the fixed effect variables are continuous: ...
28 views

How to estimate proportions of variance in outcome variable attributable to each individual fixed effect variable in lmer?

I am using multivariate models in lme4 to try to work out, quantify and compare the effects on a single outcome variable of a large group of fixed effects variables. Because the data are at week and ...
31 views

linear mixed model - post hoc tests for categorical variables against fixed value null-hypothesis

I'm fitting an LME (with lmer in R) with one categorical variable that has many (80) different values. A fitting example for my problem would be how weight loss ...
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Marketing mix model with marketing campaigns that are not consistent?

So we got sales data for six months which has 4 different marketing type campaigns running. One of them is in-store which runs for 3 months only. Another campaign is social which has the least spend ...
50 views

Random effect estimates for factor levels that don't exist

I am modeling the effect of race on test scores and would like to use a mixed or nested linear model to obtain estimates of the interaction between race and the school a student attends. I have ...
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Can top levels be fit as random effects while lower levels are fitted as fixed effects?

I am analysing a data set with a cross-classified structure, using a GLMM with a logit link. The unit of observation is clustered within two crossed hierarchies: one has three levels, the other has ...
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Applying linear mixed model for RNA-Seq data [closed]

We have an RNA-Seq data set from mouse with three conditions in triplicates. For better understanding of the reaction, each of the animal was weighted and its urea levels were measured beforehand. We ...
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How to set up my partial cross classification model in lme4 [closed]

I have a dataset with 300 individuals $i$ that provided ratings on objects $o$ that are $y_{io}$. Each individual rated a random sample of 3 objects out of 20 possible objects so that I have 900 ...
19 views

Nonparametric equivalent of mixed model for nested data?

I have collected a nested data measuring cell growth which has two levels (3 patients with disease A, another 3 patients with disease B, another 3 patients with disease C). For each patient, cell ...
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Nested Fixed-effects in a GLMER. Continuous variable nested in one level of a two-level categorical variable. Is it possible? [closed]

I am not asking for help in the coding unless that may resolve the issue. I am wondering if this is even possible from a statistics standpoint and if it is, how I go about resolving it, because all my ...
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Visualizing glmer.nb results

I'm new to the world of R and statistical modeling and struggling to find an appropriate way to visualize the results of a generalized linear mixed model with a negative binomial distribution (glmer....
27 views

Can one assume two different functions that vary by group in a mixed effects model? (e.g. Group A is linear and Group B is quadratic)

I am wondering whether you can assume two different functional relationships that differ based on a group-based predictor in a mixed effects (or any) statistical model. The goal is a predictive model. ...
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How to choose between two non-nested mixed linear models

We have a question about how to choose between two non-nested mixed linear models. The two models in R: ...
19 views

Unknown statistical test vs nested ANOVA test in Statistical software

I have a set of healthy control individuals and several different patients (with different diagnosis, so I am not trying to compare them as a group. From now I will only refer to a single patient ...
33 views

Bayesian estimation of mixed effects models covariance matrix

For a mixed model of the form: $$Y = X\beta + Z u + \epsilon$$ I know it is usually assumed in the parametric approach that: $u \sim N(0, D)$ and $\epsilon \sim N(0, \sigma^2I)$ Where $D$ is a ...
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Model simplification

I am currently looking at a linear mixed model of with the formula x ~ y * z I'm struggling with simplifying the model. When I run an ANOVA of my model it said ...
19 views

Need for multiple-comparison correction in 2x2 RM-ANOVA across individual factors/interaction?

I would like to know if it is necessary to correct the "overall" tests ofmain-effects/interaction effect for multiple comparisons in a 2x2 mixed-effects repeated-measures ANOVA. Simple example: ...
22 views

Is it necessary to fit cluster-level covariates for mixed models?

Suppose I have the following two generalized linear mixed models (GLMM): \begin{align*} g(\mathbb{E}[Y_{ij}|X_{ij}]) &= \beta^\intercal_1 X_{ij}^{(1)} + \beta_2^\intercal X_{i}^{(2)} + U_i &&...
32 views

High GLMER dispersion parameters

I am running a glmer with a random effect for count data (x) and two categorical variables (y and ...
20 views

The appropriate statistical model for categorical/binary DV + mixed design

What R function should I use to build the appropriate logistic regression model if I have the following structure? Independent variables A categorical variable that varies between-subjects A ...
20 views

How to handle unequal trials between conditions in Mixed Effects Models? R

I have a rather simple design, but I am unsure how best to (properly) handle the data analysis. I have an experiment with two between-subjects factors and one within-subjects factor. I will use, as ...
31 views

Centering and scaling each subject individually - mixed effect models

I have a repeated measures design with two factors (A,B). For each subject, variable C is measured 7 to 10 times in each combination of A and B. My first approach was to scale and center each ...
41 views

Relative importance different model diagnostics in LMM/GLMM

I may be over thinking things but I have been stuck on this issue for the last few days. I am currently modelling data with a large number of clusters but cluster size is limited to 2, with a skewed ...
43 views

Ordinal longitudinal data with unequal number of responses

I have a dataset that comprises of about 900 subjects. There are baseline independent variables which can be continuous or not (e.g. sex, age etc.). The "response" variable is a series of measurements ...
36 views

Algebraic equations for mixed linear models and when to use constraints on parameters

My issue relates to Question 4a. of Paper 1. The corresponding solution gives the algebraic equation of the fitted model as $Y_{ijk} = \mu + \tau_i + b_{ij} + \epsilon_{ijk}$ and imposes a ...
30 views

Translating multinomial logistic regression into mlogit choice-modelling format

I have an EEG dataset where I have several subjects in multiple sleep stages (~10 subjects, 5 stages). I want to see which of a number of EEG-derived metrics (measured in each subject in each sleep ...
59 views

Odds ratio confidence intervals and p-values suggest different conclusions in a binary logistic mixed-effects model (glmer)

I am running a generalized linear mixed-effects model in R using the glmer function of lme4. The outcome variable is trial-level accuracy in a task (incorrect trials are 0, correct trials are 1), and ...
64 views

Assessing a binary decission based on continuos and multi-level categorical variables

I have been asked to generate a tool to assess if a particular new set of measurements fit within a list of already accepted ones. The problem is that there are different categorical variables with ...
53 views

How to report variance components of random intercept model?

I have used: model1 <- glmer(binary~ X1 + X2 +(1|MAINCATEGORY/YEAR), data = mydata, family = binomial(link = 'logit') To get the variance components of the ...