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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How to interpret clmm output

I am using the clmm() function from the R package ordinal. I understand that the ...
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Understanding Multilevel graphs

Sorry for the simple question. Could someone help explain how I would describe the findings in multilevel model graph. I'm looking at between region variation in disease cases with temperature as ...
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How to report my repeated measures analysis?

I've conducted an experiment with 30 participants using a counterbalanced design they performed a task in two slightly different conditions. After both conditions participants were asked to fill in a ...
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Main effects in Minitab

I have a multilevel factorial design. I use Minitab to study and analyze this design. One of the outcome of such study is the main effect plot. I get the following : As I am new to design of ...
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Issue with linear mixed effects model and interaction : any alternate method?

I have a variable (Y) which I'd like to know if it can be explained by linear regression with two other variables (A and B) or the interaction of A and B. Let's say, to simplify, than I have two ...
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How to specify a simple model in lmer/lme4: do I need explicit nesting?

I am measuring response time RT_log for 3 experimental manipulations (Conditions), and there are 4 ...
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19 views

Multilevel model using negative binomial

I'm trying to look at between region variation (5 regions in total) in disease cases and the influence of climatic factors. How do interpret the variance given such a small value i.e variance when ...
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16 views

An improvised method to model heteroscedasticity in a mixed regression model

Here is a description of my experimental design: Randomized complete block design with 4 blocks/replications and a split-plot factorial design. I have the following treatments: 2 ...
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12 views

How to correctly specify random terms (intercept and slope) in mixed models for a classic psychology design?

I tried using mixed-models via lmer() from the lme4 package in R on my data, but I encountered some problems with correctly specifying the random terms effects. I ...
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Random intercept with high ICC - interpretation

I have a feeling there is a very simple answer to this question that I am overlooking. For some reason I am having a hard time wrapping my head around this, even though it's a pretty simple situation. ...
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Random effects, fixed effects, or perhaps nested fixed effects?

Simple question (I hope). I have the following experimental design: Two groups: A, B (let's say they represent the two sexes), where I randomly sampled 4 subjects from each group, and measured blood ...
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How is the intercept calculated in a generalized linear mixed-effects model?

How is the intercept calculated in a generalized linear mixed-effects model? When there are no Random Effects included the intercept is the average of the reference group, but it is not clear to me ...
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Mixed model with crossed effects and repeated measures - what is correct ‘maximal model’ for use in lmer/lme4? [R]

Objective I have a crossed and implicitly nested design and am trying to validate the correct ‘maximal’ model (including all linear and pairwise interactions of the variables) for use in ...
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Partial Least Square regression in mixed models?

As a graduate student, I am glad to have so many cool things online to teach myself. To learn about PLS, I liked the materials provided G. Sanchez (e.g., ...
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R: Can I include random effects in Firth's penalized-likelhood regression?

I have the problem of (quasi-)complete separation in a dataset with N=500 but only 25 positive outcomes (response = binomial). Including a lot of categorical factors in my model, I face the problem of ...
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1answer
25 views

SAS PROC MIXED Parameter Interpretation

I have a dataset and am attempting to run proc mixed with the intent of collecting parameter estimates for future projections. I am interested in how Y changes with X1, over various locations. I am ...
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How to justify a “complicated” regression model over a simpler model to a non-technical audience?

I find myself in the position of advocating for a linear mixed-effects model to estimate a trend to a non-technical audience. The subject of the regression model is a somewhat contentious topic and my ...
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Shall I use a random effect or not?

I need to see if in the case I am going to present it is worth to use a random effect or not. I carried out some bird counts from 9 elevated lookouts in an island. Just to orient you, these lookouts ...
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24 views

Understanding random effects lme4 model

I'm trying to understand mixed effects models in R. I have 2 questions: What is the difference between the models m=lmer(y ~ 1 + x + (1+x|g), data=r.data) and ...
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DF difference in Proc glimmix when using events/trials syntax

I am learning generalized linear mixed models using Proc Glimmix in SAS. I use an example from SAS website: ...
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issue calculating adjusted means for glmer model

I'm attempting to calculate adjusted means for a binomial outcome variable using a generalized linear mixed-effects regression analysis. I've got two interacting fixed factors and one random effect. ...
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41 views

Under what conditions are these mixed model formulations equivalent?

I see models for "mixed effects" (i.e., models with fixed as well as random factors) specified in the literature in two ways, and I'd like to understand the conditions under which they are ...
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24 views

Is it appropriate to test for collinearity in a mixed model using VIF?

My study is examining predictors of skin lesions in pigs. I am looking at the effect of predictor variables (including weight at 4 weeks, 9 weeks and 20 weeks) and I have carried out a mixed model ...
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116 views

Repeated measures - random effects for logistic regression in R?

Study design 504 individuals were all sampled 2 times. Once before and once after a celebration. The goal is to investigate if this event (Celebration) as well as working with animals (sheepdog) ...
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Using re.form= in predict.merMod() for a lmer() model

If I fit a model with a random-intercept and random-slope then use predict.Mermod with re.form = ~ (1|Subject), my gut told me ...
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Use of mixed effects model for count, continuous and binary variables

I have data in the following structure: Nested: "site" (n=6) > "year" (n=6) Response: "marshland_area" (continuous) Explanatory: "sea_level" (continuous); "invasive_species" (binary); ...
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Fixed effect not siginificant in multi-level model, what else to report besides significance?

I'm studying the effects of a teaching style intervention on student motivation. I use multi-level modeling since students are nested within teachers. The condition main effect is not significant (p = ...
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How to interpret P-value from mixed model and P-value from overall ANOVA?

I fitted mixed effect model with several effects with lme package in R by command ...
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33 views

Back-transform coefficient from linear mixed model with log-transformed response

I ran a linear mixed model (lme4::lmer in R) with a log-transformed (base 2) response, and predictors were not transformed. I want to back-transform my coefficients to make a statement about effect ...
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How do the observed values of random effects enter the computation of linear mixed models?

How do the actual values of the random variable $b$, collected from observation, enter into the maximum likelihood computations for the linear mixed effects model? Specifically, for the model ...
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37 views

Is a mixed model including repeated measures is appropriate for me, and how to interpret it?

I have a repeated measures study including 370-ish people measured twice on all variables (var1 to var6, including exposure variable), with some subjects who didn't complete the second assessment yet ...
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32 views

Post-hoc tests in mixed model using lsmeans and glht

I have a mixed model with two fixed factors (Insecte and temperature) with two random factors (bloc and date) nested in the temperature treatment. I also include interactions between the fixed factor ...
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Interpretation of mixed model output in lme4 and stan

here's my model in lme4 ...
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What is the benefit of using repeated measures in a mixed model vs. running a general linear model on the average of the repeated measures?

I have a dataset with protein measured twice from the same individual at three different timepoints. The data also includes the mean protein measure (the mean of the two repeated measures) for each ...
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Use for categorizing fixed effects that are non-linearly related to the response variable in mixed model?

So I'm pretty new to this and am a bit confused: I have a model in which some fixed effects are not linearly related to the response variable. Thus I have included the square/cubed version of the ...
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Are random slopes necessary in a counterbalanced design?

I have experimental data that includes one within-subjects factor consisting of the presentation of two different stimuli to participants. The order of the stimuli presentation was counterbalanced ...
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63 views

Nesting random effect within fixed effect using lmer() of lme4 in R

Problem I want to fit a model using the R lme4 lmer function, and I'm not sure how to specify a random effect that is nested within a fixed effect. Setup I am applying a ...
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24 views

Repeated measure with block design

I have a set of data with a full factorial randomized block design, were fertilizer and irrigation are my between-subject terms. ...
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1answer
18 views

Should I use a Mixed ANOVA?

I am struggling on which type of ANOVA to use for my work, I will provide as many details below about the study design, at the moment I am thinking mixed ANOVA but im encountering some problems which ...
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Model selection for random effects: can unselected random effects be used as fixed effects?

I am working on a mixed effects model. What I would consider random effects are year, sampling transect, and sampling location. There are multiple collections taken along each transect, and multiple ...
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Length of Time-Series for Forecasting Modeling

I'm working with mixed model for forecasting analysis. One of the decision that we want to take for the modeling is length of time-series, whether it should be 2 years or three years. So my question ...
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Inflated Type 1 error in glmer (for main effect but not interaction?)

I am doing simulations of type 1 error, power, and power' (power corrected for anti conservativity) for research on a specific application of (g)lmer, namely to small-N designs of longitudinal ...
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Choosing test to compare biological measurements at three timepoints

In my study design, I'm measuring concentrations of different mediators at an acute event (time 1) and at two follow-up timepoints (time 2 and time 3). My main question is whether the concentrations ...
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Within-subject repeated linear mixed-effects design in lmer

I would like to know more about the correct way to specify a within-subject repeated measures LME. In the study, participants (id) saw videos of 4 different conditions (each participant saw all 4 ...
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Mixed-effects model: Help with model specification

I am trying to specify a mixed-effects model and would appreciate your help: The total cohort consists of two subcohorts; the first subcohort is part of a controlled trial, in which half of the ...
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AR-M correlation structure in GEE

I am trying to use the GEE package in R to fit a GEE model to some clinical trial data. The model fits fine using independent, or exchangeable correlation structures. I'm trying to use an AR-1 ...
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Multivariate analysis with repeated measurement

Unfortunately I did not get any reply yet. I have a dataset of 900 subjects. Each on them belongs to one of the 4 categories of group1 (A,B,C,D) and to one of the 5 categories of group2 (0,1,2,3,4). ...
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Interaction term in a linear mixed effect model in R

I am attempting to analyze the effect of two categorical variables (landuse and species) on a continuous variable (...
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How to simulate data to demonstrate mixed effects with R (lme4)?

As a counterpart to this post, I worked on simulating data with continuous variables, lending themselves to correlated intercepts and slopes. Although there are great posts on this topic on the site, ...