"Mixed effects models" refers to models that have both fixed effects and random effects. They are used to model longitudinal data or data that are clustered & thus do not have independent errors.

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Why CLMM function for ordinal mixed logistic regression changes the means?

I am using CLMM to run the ordinal mixed logistic regression model as the DV is ordinal number from 1 to 9 (rating scale). First I read the file and change the DV into ordinal using these commands: ...
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12 views

Backing out fixed / random effects in lmer mixed model

Assume that I have a linear mixed model of the following form, specified using lme4: fit <- lmer(A ~ B + C + (1|D) + (1|E), data=data) I am struggling with ...
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12 views

Obtaining significance for mixed GLMMs on count and binary data

I'm new to the software R and am trying to compute statistics on data from experiments on the offspring of lizards from two different thermal treatments - looking specifically at differences in their ...
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7 views

Mixed effects model, pseudoreplication in space, change through time

I have not found a good example for data with my structure. The data come from a long-term observational study. The response variable is growth rate, with one measurement from an individual fish. ...
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8 views

Hypothesis testing in GLMMs - How to set up sequential LRTs

I'm fitting a generalized linear mixed effects model to my data. I have three fixed effects, and one random effect nested within one of the three fixed effects. The response variable is a count, ...
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18 views

Simple effects of categorical interaction

I have two two-level categorical variables, IV1 and IV2. I want to fit a linear model in R and find out the simple effect of IV1 on the DV at each level of IV2, separately. I'm not interested in the ...
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14 views

Model fit becomes better after adding a fixed effect

I fit the following model to the repeated measures data: $$Y \sim A + (B|id) + (C|id)$$ However, if I add a fixed effect of B in the model: $$Y \sim A + B + (B|id) + (C|id)$$ quality of the fit ...
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17 views

GLMM with Gamma distribution vs. Gaussian distribution with log transformation

Is there really a difference in result if I use a GLMM with Gamma distribution vs. a model with a Gaussian distribution with log transformation? If so, how do I choose between the two methods? See ...
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43 views

How can I test variance explained by the factor group if each subject in the group comprises a different number of measurements?

The data structure I have 2 groups with 30 subjects each. Each subject has a different number of fibers (approximately 46000 +/- 3000) of different length (see histogram). My goal is to determine how ...
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34 views

Testing the variance component in a mixed effects model

Say $y=X\beta+ Zu +\epsilon$ is our mixed effects model where $u=(u_1,..,u_r)$ and $u_{j} \stackrel{i.i.d.}{\sim} N(0, \sigma^2_{a})$ for $j=1,...,r$ and $\epsilon=(\epsilon_1,...,\epsilon_n)$ are ...
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60 views

Estimates of the variance of the variance component of a mixed effects model

Say $y=X\beta+ Zu +\epsilon$ is our mixed effects model where $u=(u_1,..,u_r)$ and $u_{j} \stackrel{i.i.d.}{\sim} N(0, \sigma^2_{a})$ for $j=1,...,r$ and $\epsilon=(\epsilon_1,...,\epsilon_n)$ are ...
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140 views

Linear OLS v Mixed-Effects Model with Correlated Regressors

Reading this post by @gung brought me to try to reproduce his superb illustrations, and led ultimately to question something I had read or heard, but that I'd like to understand more intuitively: Why ...
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15 views

Do I have heterogenity in my GLMM? And if, how do I fix it?

I'm fitting a GLMM model with overdispersion and excess zeros (using R packagae glmmADMB)and I think I have heterogenity. Here is a plot with all my IV against residuals (alls IVs reflect count ...
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2answers
40 views

specification of mixed effects model with two levels of repeated measures (in R)

My colleagues and I conducted a study of the effects of an experimental translocation on the movement and activity patterns of common brushtail possums in New Zealand. This involved first capturing 12 ...
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39 views

Need help selecting appropriate statistical method for animal study

I could use some help deciding on the proper statistical method for a current experiment. The experiment is setup as follows: Independent Variable: Diet (4 groups of 10 for a total of 40 animals) ...
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20 views

Mixed effects model for repeated measures to test for factors that are either constant or dynamic within an individual over time

I am dealing with a rather complicated dataset with repeated measures of the same individuals at various time points (samples were collected at different time points and different number of samples ...
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17 views

marginal R2 = conditional R2 in mixed model

Is it possible that the marginal and conditional r squared are the same in a mixed model? I get that situation a few times when adding a spatial autocorrelation structure to the model. Without this ...
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41 views

Longitudinal data analysis

I have a question regarding longitudinal study analysis. I tried to search similar questions like mine but didn't really find it. So here is the brief description of data and my question: I have a ...
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15 views

Non-nested model with uniquely identifying groups

I'm testing various specifications of linear mixed effects models with lmer() in R. The data are fiscal year firm-level, so ...
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9 views

What's the drawback of using interaction terms to analyze the pre-post control data?

I am trying to analyze the data with the pre-post-control design in the context of RNA-seq analysis. I have read Best practice when analyzing pre-post treatment-control designs, but I am still ...
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9 views

Structural zero design in mixed effects model

I would like to do a mixed effects regression that is like this: ISI ~ Location + Stage + Stage*Location + 1|Patient/Chan Where Location and Stage are fixed ...
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18 views

Distinction between fixed effects and random effects for continuous predictors

The distinction between fixed effects and random effects seems intuitively clear to me. A factor is a fixed effect if the set of possible levels for the factors is fixed. A fixed effect factor would ...
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27 views

Mixed-effects in SAS

I am analyzing weekly data on 50 products which were sold in a number of shops during one year. My goal is to estimate a mixed-effects model for unit sales with heterogenous AR(1) error structure. ...
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94 views

When and why do I have to use “trait” for multinomial multilevel models with MCMCglmm in R?

I want to estimate a multilevel multinomial logit model but I am struggling with the terminology and notation used by the R-package MCMCglmm. There is documentation ...
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20 views

Different results in a mixed model when compared with raw data

I ran a model with reaction time as my DV and PWI Condition (2 levels) as one of the fixed factors. I used contr.sum for all fixed factors. I ran the following model to look for differences in ...
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Interpretation of deviation coded data in mixed effects models

ran a model with reaction time as my DV and PWI Condition as one of the fixed factors. I used contr.sum for all fixed factors. I ran the following model to look for differences in reaction time ...
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29 views

reporting mixed effects linear regression: t statistic or model comparison?

We have a one factor three level repeated measure experiment with ratio data (reaction times). We fit a mixed effects linear model using lmer (in fact lmerTest) - maximal, with subjects and items as ...
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107 views

Binomial Temporal GAMM does not converge (R::mgcv)

I am new to both mixed effect and Additive models so I'm sorry if the answer here is trivial. I have data collected on several metabolic chemicals (M1,M2...), covariates (time,Race,Gender...) and ...
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22 views

Mixed effect modeling SPSS: within-individual

I’m new to mixed effect modeling in SPSS and wonder if anyone could assist me with the analysis: I have longitudinal data from one country as follows: For 20 time points [years] I have the average ...
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20 views

Pseudoreplications and the methodes used to explore the correlations

In my experiment I have measured growth of different trees on predefined circular plots (x, y, z, a). On each plot all trees were measured. For each location I have one treatment information. Now ...
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17 views

Effects of covariance structures on mixed effects models

What are generally the effects of using a covariance structure on a mixed effect model ? More specifically, in a mixed model, what should be the expected effect of using an AR(1) covariance ...
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73 views

How to backtransform data that has been log transformed in order to report raw values for ease of interpretation?

I have run some lme4 analyses on reaction time data in R, with RT being the main outcome variable of interest, which I first log transformed due to non-normality ...
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68 views

Lmer v. lm with Dummy Variables. Where Does the Math Differ in a Simple Example?

I am trying to understand the concept of mixed effect along with the R syntax in lme4 with simple scenarios out of the dataset ...
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67 views

lme4: Why won't lsmeans output my fixed effects?

I'm trying to plot confidence intervals for linear mixed effects models trained with lme4 and lmerTest in R. I am using this data file, which I've shared via Google Drive. Here is my trained model. ...
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47 views

Mixed-modeling when no observation contributes both X and Y

I'm working on a project investigating the relationship between (let's say) a face's perceived masculinity and its perceived competence. There was a large number of face stimuli (80). Two completely ...
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48 views

Random slope and random intercept correlation at every level of X

Lets say individuals are nested within each ID and I am trying to a predict level 1 outcome Y from a level 1 predictor X1 or X2 with random slopes and intercepts. X1 and X2 are equivalent to each ...
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2answers
53 views

Need help with nested random/mixed effect model specification

I am a newbie in meta-analysis and I need your opinion on the design of my random-effect model. I have conducted an experiment on the performance of a provider who has around 30-40 data centres. I ...
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1answer
60 views

calculating adjusted means from lmer

How can I calculate adjusted means for a regression model with fixed and random effects? I'd like to calculate the adjusted means for a lme regression with this formula ...
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17 views

Mixed Effects Poisson on error data

I have data from a 2 x 2 repeated measures factorial experiment. There are 20 participants who each completed 24 trials for each one of the following factor combinations. 1) A1 x B1 2) A1 x B2 3) ...
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67 views

Mixed effects model: model fitting vs conceptual sense

I have a data from a 2 (load) x 2 (comp) x 2 (sal) full factorial repeated measures experiment and I'm trying to fit a linear mixed effects model to it. Here is a sample of the data: ...
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35 views

Understanding variance estimation by restricted maximum likelihood (REML)

I'm reading Doug Bates' theory paper on R's lme4 package to better understand the nitty-gritty of mixed models, and came across an intriguing result that I'd like to understand better, about using ...
3
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1answer
116 views

Mixed effects model hypothesis testing

I ran a 2 x 2 x 2 full factorial repeated measures experiment where 20 participants were exposed 30 times to all combinations of the factors A, B and C in random order. This is a standard procedure in ...
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1answer
50 views

“Pairwise not statistically different” leads to “overall statistically different”?

I have a linear mixed-effect model $$ y=\beta_0+\beta_1x_1+\beta_2x_2+\beta_3x_3+Zb+e, $$ where $[x_1\ x_2\ x_3]$ represents the fixed effects, and $Z$ represents the random effects. Now, I test the ...
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42 views

Testing outlier influence on random effects in linear mixed effects models

I have been reading a little bit about diagnostics for linear mixed effects models and have started wondering about how outliers may influence random effects in addition to fixed effects. The paper on ...
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1answer
46 views

Repeated measures through time using mixed effects in R, plus post hoc tests

I have been trying to figure out how to do a fairly basic repeated measures analysis using linear mixed effects in R, and then analysing it using post-hoc tests. The problem is that I'm not sure ...
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58 views

What's an example of a situation in which it makes sense to assume random slopes but a fixed intercept?

I'm referring to multilevel modelling. Field (2013) writes: It’s worth noting that it would be unusual in reality to assume random slopes without also assuming random intercepts, because ...
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22 views

GEE Logistic Model with Subject Specific Predictions?

I have fit a marginal logistic model or GEE Logistic Regression model using SAS' proc genmod to obtain estimated parameters associated with mortality (death). Using SAS, I am able to obtain ...
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46 views

Rule of thumb for sample size for mixed-effects logistic regression analysis?

Is there a simple way of calculating the minimum number of participants (and/or items) needed for a mixed-effects logistic regression analysis? In particular, what should I do if I don't know what to ...
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shall I add all correlated variables in a mixed effect model?

If I have a mixed effect model case with various predictor variables. If some of the variables are correlated; is it better to add both correlated variables to the model? or shall i take out one of ...
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I'm having trouble fitting a general (not generalized…) linear mixed-effect model using the lme4 package. Can anybody help?

I need to fit a linear mixed model in the "Laird and Ware" framework. This type of model is usually specified by (as you may know): $\mathbf{y}_i = X_i \beta + Z_i \mathbf{b}_i + \mathbf{\epsilon}_i ...