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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Fitting mixture distributions and probability estimation

I am working on continuous data set with ranges 0-1. I need to group them using mixed models (based on prior clinical/biological basis). From this model, I need to get the p-value for a value (say ...
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Random effects in GAM [on hold]

I am now trying to use random effects in GAMs developed by Professor Simon Wood. Prof Wood uses s(...,bs="re") to account for the random effects. Random intercepts models or random slopes models are ...
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linear mixed model main effect in same column

I am trying to build a linear mixed model in R comparing the influence of a athletes playing level on running output. I have done this analyses previously, but now we are including this playing level ...
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54 views

Using lme4 correctly for a nested mixed model

I'm trying to create a nested model in lme4 and would like feedback on whether I've understood its use correctly. Every individual (n = 144) had two proteins measured after 0, 12 and 72 hours. At ...
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pre-post vs single measurement control group. Help!

I have been asked to help a PG student with statistical analysis of her data, and I am really struggling to know the best way forward. The design is unbalanced, and I am not sure if there is a way ...
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38 views

A model for repeated treatments and repeated outcomes

I have the following data: Measurements of kidney function (in units called GFR) taken at several time points pre-operation (not evenly spaced) and at several time points post-operation. Here's my ...
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17 views

How to fit 3-level factor in lmer of lme4 with zero correlations between random slopes?

I'm trying to fit a linguistics model with a 3-level fixed factor (Condition) in lmer(). There are 20 Subjects and 12 Items, in ...
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18 views

Mixed model with clustered and repeated-measures data

I'm analysing the results of an experiment using a mixed model. Reaction times for each subject (40 male and 40 female) to 8 stimuli have been registered. The process has been repeated on the same ...
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Mixed Effects Model R Help [closed]

I am trying to formulate a mixed effects model in R in order to determine the repeatability of individual personality traits. I have 4 measurements for each individual and I measured 6 personality ...
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How is correlation between fixed intercept and fixed effect calculated in lmer of R, lme4?

When I fit any model in lmer(), summary identifies a correlation between fixed effect(s) and the (fixed) intercept. How should ...
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12 views

How to interpret clmm output

I am using the clmm() function from the R package ordinal. I understand that the ...
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16 views

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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28 views

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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28 views

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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36 views

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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18 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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14 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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19 views

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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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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42 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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26 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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117 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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1answer
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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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27 views

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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36 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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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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1answer
33 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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67 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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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 ...