"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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Predicted probabilities for probit model in R - categorical variable

I am running a probit regression with a random effect: m1<-glmer(Binary~Explan+(1|Random),family=binomial(link="probit")) where Explan is a three-level ...
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46 views

Survival Cheat Sheet ANOVA Alphabet Soup & Regression Equivalents

Can I get help completing this tentative (in progress) attempt at getting my bearings on ANOVA's and REGRESSION equivalents? I have been trying to reconcile the concepts, nomenclature and syntax of ...
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20 views

mixed model formulation

I have 7 groups (groups), 20 fish in each group (fish.ID), 25 cells from each fish, and 4 measurements from each cell corresponding to head (head.len), ubody (ubody.len), lbody (lbody.len) and tail ...
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10 views

Correlation between standardized residuals and fitted values in a linear mixed effect model: Course of action?

I am fitting a linear mixed effect model in R with lme from nlmer, using the approach described in Zuur et al. "Mixed Effects ...
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62 views

Computing likelihood of a mixed-effect model manually

My question has to do with how to manually compute the likelihood of a mixed-effect model. I understand how to determine the likelihood of a fixed-effect model manually. For example, if I make up ...
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14 views

How do we do residual analysis for linear mixed effect models (small sample size)?

Can anyone please explain me how to do residual analysis for the dataset that has small group size (like two samples per group) and around 10-15 groups in total? Now the errors are correlated within ...
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74 views

How compute the Intra-Class Correlation for a Negative Binomial Mixed Model in lme4

I have a negative binomial mixed model with counties nested within states. I've read that the formula for the ICC for a negative binomial model is: found here: ...
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20 views

Choosing a reference group among categorical fixed variables in a linear mixed effects model

I am working on a project that uses a linear mixed effects model for its main analysis. I am looking at the impact of situations on 'trait' and the random effects variables are participant ids (pID) ...
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13 views

How can I get a GraphPad-like result output with R using a two-way mixed model ANOVA?

Design of the experiment is as following: 11 groups of 3 mice (10 groups each infected with a different virus and 1 control group), so a total of 33 different mice 15 tested time points, from day-6 ...
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35 views

Model selection in mixed-effects model with collinearity trouble

In a model aimed to assess the influence of land use measures on ecosystem functioning, I have one log-transformed dependent variable (the ecosystem function), and 5 fixed-effects independent ...
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26 views

How to turn nlme syntax into manuscript appropriate equation?

I ran an linear mixed-effects analysis in R using the nlme package. I would like to write out the algebraic equation of the model's specifications. Unfortunately, I do not know exactly how to ...
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17 views

Calculating effect sizes for mixed effect logistic regression to determine subsequent sample size

We conducted a previous preliminary study using 40 participants. We analyzed the data using the lme4 package in R to conduct a mixed effect logistic regression. We ...
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33 views

Mixed-effects models with customer data: how do choices affect the model?

Suppose I had a large sample of customer data from which I want to predict total amount of sales over a time period with predictor variables indicating: -which sales channel did customers come from ...
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24 views

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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14 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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19 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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13 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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12 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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23 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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16 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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39 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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44 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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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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73 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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152 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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44 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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22 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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26 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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43 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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17 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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13 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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10 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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22 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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34 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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110 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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12 views

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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32 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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113 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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26 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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21 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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21 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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91 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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99 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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48 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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56 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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59 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
72 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 ...