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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4
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1answer
34 views

Is my design nested or crossed? Question concerning specifying random effects with lmer in R

I've run an experiment where 120 participants (PP) viewed 40 quotes (Item) each (presented in Facebook format) and were asked to ...
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33 views

Different linear mixed model approaches for only estimating variance components once

I found these papers on linear mixed model with a single random intercept: 1. https://www.genetics.org/content/177/1/577.long Where they use an approach for implementing a linear mixed model, where ...
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1answer
34 views

Repeated measure clinical trial Linear mixed model

I am working on a clinical trial testing an innovative rehabilitation therapy on patients and I would like some suggestions on how to analyse the data. The study design is: 2-groups: conventional (n=...
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2answers
176 views

Why not always use generalized estimating equations (GEE) instead of linear mixed models?

I read about generalized estimating equations (GEE) here, here and at other sites. It is mentioned in first of above links that "the parameter estimates are nearly identical" for linear ...
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1answer
27 views

Standard error in multi-level models vs. non-multi-level models

Gelman & Hill (pp. 252-259) discuss "no-pooling" (single-level), and "partial-pooling regression" (multi-level) with no predictor ($section~ 12.2$). In almost all mixed-effects ...
3
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1answer
48 views

spaMM::fitme() - error troubleshooting and application to longitudinal data [closed]

I'm trying to fit a GLMM that accounts for spatial autocorrelation (SAC) using the spaMM::fitme() function in R. I have a longitudinal data set where observations were collected repeatedly from a ...
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1answer
65 views

Does sample size affect choice between fixed and random effect

I am analyzing data as given in this question: Should "City" be a fixed or a random effect variable? Here it is debatable whether "City" is to be kept as fixed effect or random ...
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0answers
41 views

Which model and distribution to use to fit continuous proportional data with random effects; glmmTMB, glmer, lme? I am getting errors with all 3

I am having trouble determining the most appropriate model to fit my continuous proportional data. I am analysing the proportion of time individuals were detected within an acoustic receiver array ...
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3answers
565 views

Should “City” be a fixed or a random effect variable?

I am analyzing data on "BloodSugar" level (dependent variable) and trying to find its relation with "age", "gender" and "weight" (independent variables) of ...
2
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1answer
41 views

Is this correct use of linear mixed model?

This is the current data I have I want to know if fixed factor A has any effect on C. That is, if A1 = A2 = ... = A5. I think I am trying to find a group difference, correct me if I am wrong. ...
2
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1answer
32 views

R - Data Simulation with Multiple Random Slopes

I am trying to run the following model: I(week^2):mutation_status + (week + I(week^2) | subject_id) , data = sim_dat) This is the output I ...
3
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1answer
32 views

Comparing model performance: do fixed and random effect regression models give different model ranking?

I am a graduate student in animal science. I am comparing linear models that fit covariates of var1 and var2. These two covariates are decomposed from one quantity say F (inbreeding level of animal). ...
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27 views

Multilevel hierarchical simulation? What model to use?

The problem: I have a dataset that I think could be deemed hierarchical. Assume that there are 1-100 ids, which all can have anywhere from 1-3 sub_ids. Both the top ids can have specific features that ...
4
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1answer
65 views

Non-normality in linear mixed models/GLMM

I have some data of time-depth profiles of whales. I want to model how the maximum depth of each dive (deepest point reached during a dive) changes between two dive types, foraging (if the whale feeds)...
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2answers
68 views

Correlation of two continuous variables but with clustered data

I want to correlate two changes in time, a change in microbiota with a change in some marker. There are several time points, so I have several differences in each participant. My idea is to see if ...
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0answers
46 views

Comparing lmer and LCMM (single class) models

I am modeling the same dataset using both lmer and LCMM. My understanding is that if I use class count of 1 for LCMM, the models derived from both methods should be very similar. However, as seen in ...
4
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1answer
147 views

Difference between Repeated measures ANOVA, ANCOVA and Linear mixed effects model

What is the best way to analyze these data: Subjects are divided in two "Group" (Treatment A and B). "Weight" is recorded before and 3 months after treatment. Outcome variable: ...
0
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1answer
36 views

lme4: prevent 'glmer' to have zero estimated random coefficient

I use the glmer function with the Poisson family from lme4. My simulated data are constituted of 3600 individuals, and a ...
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0answers
22 views

Preparing **probabilities** data for mixed effect modeling

I have two related problems i cant seem to find an online solution and would really appreciate any direction. I am modeling probabilities* as a function of different predictors, across 35 subjects. X1 ...
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0answers
29 views

glmmLasso vs. lmmLasso vs. LMMEN to reduce highly correlated predictors?

I have trouble choosing the correct model and parameters for my problem. I have around 20 experts who rated the quality of brain tumor segmentations for around 20 patients on a 1 to 6 star scale. I ...
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0answers
17 views

How to model repeated measurements with the same outcome in a Bayesian framework?

Can't think of a more accurate title, so I'll illustrate the problem with an example. I want to record temperature using cheap noisy sensors. I also have recordings from a gold-standard reference ...
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0answers
36 views

Estimating a paired samples t-test equivalent in mixed model with two random factors

I have data where 880 participants answered 10 questions at time 1 and at time 2. I want to use a mixed model and consider both participants (id) and questions (question) as random effects. I'm using ...
3
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2answers
57 views

Follow-up: Complete-pooling, no-pooling, and partial-pooling regression in R

This great answer demonstrates the concepts of "complete-pooling regression", "no-pooling regression", and "partial-pooling regression" (3 concepts) using simulated data ...
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1answer
24 views

How to interpret main effect with two interaction terms?

I have three variables in a multilevel model: Relationship Status (0 = single, 1 = not single) Living Arrangement (0 = alone, 1 ...
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0answers
41 views

Autocorrelation in linear mixed models (lme)

To study the diving behaviour of whales, I have a dataframe where each row corresponds to a dive (id) carried out by a tagged individual (whale). For each dive I calculate a series of parameters (...
3
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1answer
37 views

Are priors in Bayesian inference similar to levels in mixed-effects models?

I often see a frequentist multi-level model (MLM) structure is defined like so (made up parameters): $$ \theta_i \sim \mathcal{N}(10, 2.5) $$ $$y_{i,j} \sim \mathcal{N}(\theta_i, 0.5) $$ But this is ...
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1answer
56 views

Is it appropriate to consider animal ID as random effect group level for mixed model?

My gene expression data are set up as 24 animals with independent Animal.ID assigned to 3 "Status" groups (8 animals each) based on herd test results. Each status group receives Treatment or ...
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1answer
14 views

How to interpret interaction in the absence of main effect? Multilevel Modeling

What is the substantive interpretation of an interaction in the absence of a main effect? Statistically I understand that the interaction modifies the main effect, but how to interpret this from a ...
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1answer
47 views

How to deal with autocorrelation in mixed models

I am trying to model a varible (maximum depth) as a function of type of dive and diel changes (day,night) with the individuals (whales in this case) as a random factor in R. I tried first to apply a ...
4
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1answer
47 views

What does a p-value of exactly 0 mean - lme (nlme) function fixed effects

Using the nlme package in R, I ran a multilevel regression model model with a random intercept and a fixed linear effect of time with REML estimation: ...
1
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1answer
38 views

All p-values of linear mixed models equal to 0

I am trying to model a varible (maximum depth) in function of type of dive and diel changes (day,night) with the individuals (whales in this case) as random factor in R. I tried to apply a linear ...
0
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0answers
18 views

Outlier in random effect - GAM

Is there any advice on how to deal with outliers in a generalized additive model? I have been following the book "Generalized Additive Models : An Introduction with R, Second Edition" by ...
2
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1answer
32 views

Random effect structure without correlation between intercept and slope

My two models are roughly like this: Y ~ A + (C+B||participant)+(1|B) and Y ~ A + ( C+ B || participant) the difference being ...
3
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1answer
14 views

Visualising mixed model with only random slopes?

How can I visualize a mixed model with random slopes for a variable but no fixed effect for that variable in a simple model such as y ~ 1 + (var | subject)?
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1answer
20 views

Including a baseline covariate in a linear mixed-effects model

I have a question on modelling a big data set (about 5000 subjects). I want to model a random intercept+slope, many of the subjects have only two observations (baseline and one follow-up), but some ...
2
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2answers
58 views

Choosing lmer model for repeated measurements with interactions

I am modeling the longitudinal data attached below with lmer model. Time_point increases in steps of 6 months. I wish to compare Groups 2, 3 scores to group 1 in time, taking into consideration age at ...
4
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1answer
62 views

Doubt regarding mixed modeling format

Say, I have a dataset that looks at how many times my 5 babies chases a cat around the house . I'm trying to estimate 'y' which is the number of times the cat runs one complete round around the house ...
6
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1answer
110 views

Demonstrating complete-pooling, no-pooling, and partial-pooling regression in R

Gelman & Hill (pp. 255-259) demonstrate in R how to achieve a "complete-pooling regression", "no-pooling regression", and "partial-...
3
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1answer
33 views

A figure or narrative to compare multi-level models and fixed-effects ANOVAs

TL;DR: What figure or narrative can represent a fixed-effect ANOVA if we represent $complete~pooling$, $no~pooling$, and multi-level (partial pooling) models using the following figures (and ...
5
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1answer
67 views

Alternative to Mixed ANOVA without homogeneity of variances

As is tradition on these posts, I should say I'm relatively new to statistical analysis at this level so if I don't provide enough info off the bat bear with me. So I've conducted an experiment ...
4
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1answer
34 views

Are time points nested in students or crossed in a longitudinal multi-level model

I often hear that in a longitudinal multi-level analysis, time points (as a fixed factor) are "nested" within students (e.g., just search the word $nest$ in this paper). However, this great ...
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0answers
36 views

minimal detectable effect size in linear mixed model

I'm trying to find the minimum detectable effect size (MDES) given my sample, alpha (.05), and desired power (90%) in a linear mixed model setting. I'm using the ...
2
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1answer
64 views

Interpretation of coefficients in mixed-effects model with circular response?

I have a dataset from an experiment where wild ants were surveyed continuously for 24 hours under a number of temperature treatments (chambers). Whenever an ant was observed, the species of the ant ...
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0answers
18 views
6
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1answer
176 views

Linear Mixed Effect Model - random intercept and slope? Identifiability problems

I have a question regarding model building for a large dataset including about 5000 Subjects. I want to fit a LMEM including multiple variables and I have repeated measurements in time. But for some ...
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1answer
16 views

How to test “nesting effects” in a linear model after you have reduced the IV by factor analysis?

I have a couple items (let's say 10) had run in a study and I want 1) to reduce the dimensions by factor analysis. Then I have two factors (let's say factor A has 3 and factor B has 7 items). After ...
5
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1answer
42 views

Nested or Crossed Effects with Nationalities

I am working with mixed effects models and I am still a bit confused. While I have read multiple explanations of what the differences between nested and crossed random effects are, I am not sure how ...
1
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1answer
19 views

Plot the probability (success) of a binary variable from coefficients of a GLMM?

I have developed a GLMM (Mixed Generalized Linear Model), as you can see in more detail [here] (Is it correct to evaluate differences of a binary variable between different places with a GLMM?) ...
2
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1answer
26 views

Nesting random effect within fixed effect, with additional nested random effect. Nominal logistic

Very new to R so please pardon my naivety. I am trying to run a sort of mixed effects nominal logistic regression model with my insect response data. I have 2 rearing treatments (hot and cold) and 3 ...

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