"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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Using a mixed effects regression model for between-subject design?

I have data from a between-subject experiment, where every subject was assigned to one of the two conditions, and completed varying number of trials (as much as they wanted). Number of trials is ...
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2answers
57 views

Using glmer, why is my random effect zero?

We’ve run a mixed effects logistic regression using the following syntax; ...
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1answer
52 views

The biological significance of ANOVA 3-way interaction

Dear statistics experts, I have trouble to find a sensible statistical approach to back up some very obvious (at least to my eyes) interpretation of a dataset (see descriptive plot below). I measure ...
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Aligned Rank Transform with random factor

In an aligned rank transform preceding a two-way ANOVA, the procedure is: save residuals by performing a standard ANOVA use Aggregate to determine effects for group means (mij for interaction, ai ...
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1answer
60 views

lme() with several within and between (categorical and continuous) subject factors

I am currently trying to analyse data from an experiment of mine and I have done some searching for instructions on the usage of the lme() function for R, since I am looking to analyse my data with a ...
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2answers
169 views

Interpreting the random effect in a mixed-effect model

I am looking at several dependant variables for which I created LMMs of the following kind: DV ~ Group + (1|Subject) + (1|Time) Now I am struggling with how to ...
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21 views

Reporting Fixed Effects as (partial) correlations?

I'm doing a linear mixed effects analysis in which I'm really only interested in one of the fixed effects. I have several other fixed effects and a random intercept term, but none of them are ...
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1answer
23 views

Random effect with zero SD in LMM

In my mixed-effects model there are one fixed effect and two random effects (subject and time of measurement). fit <- lmer(DV ~ group + (1|subject) + (1|time)) ...
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1answer
231 views

Likelihood and estimates for mixed effects Logistic regression

First let's simulate some data for a logistic regression with fixed and random parts: ...
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25 views

How to nest hierarchical data variances in R

Apologies ahead of time for not having an exact data set as this is more of theoretical question that I stumbled across while working on mixed effects models. Suppose I have the following data ...
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32 views

Fitting mixed effects logistic regression with random effects

I have a data frame of 134 observations, 9 independent variables, and a binary, categorical response; please see its structure below: ...
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55 views

Why and how does the inclusion of random effects in mixed models influence the fixed-effect intercept term?

The question is best illustrated by this example which uses a dataset (in library faraway) and lme4 library (both in R). This ...
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126 views

Mixed effect linear regression model output interpretation

I just fitted the following linear mixed effects model: ...
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1answer
74 views

Number of observations in groups - linear mixed effects model

I would like to fit linear mixed effects model to my dataset, but I was wondering if quantity of observations in groups matter? I have some groups with about 60 observations in each, but there are ...
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9 views

Appropriate df for a linear mixed model when looking at variance

Suppose I fit a linear mixed model as: lme(Response ~ 1 , random = ~1| Location | User | Machine). Thus machine is nested within user which is nested within ...
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1answer
39 views

How to compare different nlme models ?

If there are 2 nlme models with same non-linear mean function, model 1 and model 2, how do you compare them ? Which R function does this for us ? And when there are random effects or fixed effects, I ...
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1answer
97 views

mixed effects model output

Let's say we have this: ...
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14 views

IT-AIC approach for mixed effects model

I was reading around the Information Theoretic-AIC approach of model selection where AIC values are used to select the candidate set of models. I am quite clear on this. My question is this: for ...
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1answer
39 views

Why do my ANOVA tables keep returning $\chi^{2}$ values of 1?

I'm using ANOVA to test for differences between different values of the same factor for a mixed effects model which I produced. My model is: ...
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40 views

Intuitive feel in mixed effect models

This is something I have been thinking about for sometime. Consider the random effects model $y= Zu + e$ where $u \sim N(0, \sigma^{2}I)$ and $ e \sim N(0, \epsilon^{2}I)$ I now want to compare 2 ...
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1answer
55 views

Experimental design and mixed models

I want to test effect of 3 PH on larval development. I would like to know what is the best experimental design and statistical analysis. We can only use 3 compartments of sea water, each one with a ...
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59 views

Different p-values between Wald Z and Wald Chisquare

I have used lme4 for mixed effects models of reaction times and accuracy rates. I could not use lmerTest because the type of model I was using are not yet implemented there (problem with predictors ...
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1answer
117 views

Mixed effects modelling; what to do when model is over-specified?

I'm trying to use mixed-effects modelling to analyse some data. There are a number of variables that I need to specify within the model, two of which are between-participants (...
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Satterthwaite vs Kenward-Roger approximations for the df in mixed effects models

The lmerTest package provides an ANOVA function for linear mixed effects models with optionally Satterthwaite's (default) or Kenward-Roger's approximation of the ...
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50 views

Help in fitting multilevel model using the MCMCglmm library in R

I am trying to fit a multivariate model using the R library MCMglmm. The data I have are testscores from c.a. 4736 students from different schools. For each student, also the socio-economic status ...
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36 views

Why are 'random' and 'repeated' in mixed models in SAS both producing the same result?

Why does SAS random and repeated both produce the same result? Can someone explain this in detail? For example: ...
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22 views

How to obtain estimates for all levels in a mixed effects model that uses effect (deviation) coding?

I am running a binomial mixed effects logistic regression in R using glmer for a sociolinguistics project. I was asked to used deviation (effect) coding. From what ...
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1answer
52 views

How do I enter a continuous variable as a random effect in a linear mixed effects model?

I collected data on the growth of juvenile fish from 4 different types of crosses using multiple distinct family blocks and I am trying to see if cross type has an effect on growth using linear mixed ...
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1answer
45 views

Interpreting the mathematical formula of a mixed effect model

I am a bit confused about the function of a parameter in setting up a linear mixed effect model (hierarchical/multilevel model). This is how I understand a (random intercept and slope) multilevel ...
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52 views

Comparing slopes in mixed-effect model

My data looks like the attached picture. The dependent variable indirectly measured physical activity. I tried to use mixed-effect model rather than RM Anova, because my actual data is imbalanced. ...
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Site effect in GAM model

I am trying to build GAM model to see the effect of several environmental variables on the total abundance of one species. I have collected samples from three sites with three replicates from each ...
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58 views

In an experiment w/binomial responses, some subjects gave the same answer for all trials. [How] can a Mixed Effects model (R's lmer) deal with this?

I recently ran a pilot of an experiment on Amazon's Mechanical Turk. In the experiment, participants read 5 items, and answered a yes/no question about each one. A between-participants factor was ...
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25 views

Testing the random slope with correlated random effects

I have a mixed/random effects model $$\mathbf{y}_i=\mathbf{X}_i\boldsymbol\beta+\mathbf{Z}_i\mathbf b_i+\boldsymbol\epsilon_i,$$ where random effects $\mathbf b_i$ has variance-covariance matrix ...
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14 views

What do I do if my sample for cross sections is not random in a panel regression model?

I am trying to implement a panel regression model, but there is one issue: both fixed effects estimation (FE) and random effects estimation (RE) require that the cross section sample be random. For my ...
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1answer
152 views

anova type III test for a GLMM

I am fitting a glmer model in the lme4 R package. I'm looking for an anova table with p-value shown therein, but I cannot find ...
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1answer
38 views

Fitted values of 'lme' function result

I fitted a linear mixed model with R as follows. ...
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1answer
59 views

SAS Proc Mixed model interpretation

I'm fitting a linear mixed model by SAS. There are 596 sectors and 8489 subjects. (each sector contains 10~15 subjects). Each subject is measured at most 6 times, so the total number of observation is ...
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31 views

Should I control for random effects of participant in an individual differences design?

I'm trying to analyse a survey study in which I'm interested in the way that individual differences between my participants influence how they respond to my stimuli. The stimuli are pieces of writing ...
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38 views

Can i use a mixture model for when I have an omitted variable?

I plan to fit a GAM or GAMM. There is one categorical variable which I think is important for explaining Y (or Y*), but it is not in my dataset - it is measurable but has not been measured. Can I use ...
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1answer
117 views

How to analyze interdependent interaction terms of lmer model

Assume I test a number of patients repeatedly over time to see how a certain treatment changes their skin conductance in response to a certain colour (cond) after 2 ...
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1answer
288 views

Coefficients from glmer in R

In a mixed effect model where the intercept is random effect and the slope is fixed effect (see the code below), I understand the output of summary(glmer(...)). But ...
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152 views

R: glmulti for mixed models returns several best models, Automated Model Selection (multilevel analysis, hierarchical model, nested data)

I searched the entire web including this forum on some help on how to use the glmulti package in order to identify the "optimal" fixed part of a mixed model with a given random part. However, I could ...
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2answers
131 views

Multilevel models including random slopes: how to calculate variance

In a linear mixed model, you take the covariance between data into account by adding a random intercept per cluster. For example, you measure the effect of a drug campaign over time on students, and ...
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1answer
24 views

How to test for relationship between cumulative intake and outcome over time in single arm study?

I have a one group trial with n = 100. I want to analyze the relationship between the accumulated amount of drug intake (continuous) and the effect (measured by symptom score). For example, for ...
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1answer
82 views

Investigating covariates in mixed effect model

Having read through a few posts, I still couldn't find an answer to my question. I'm trying to investigate for the effect of covariate C on a longitudinal dataset. I have two linear mixed effect ...
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1answer
123 views

Plots to illustrate results of linear mixed effect model

I've been analysing some data using linear mixed effect modelling in R. I'm planning to make a poster with the results and I was just wondering if anyone experienced with mixed effect models could ...
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34 views

GEE Combined with Linear Mixed Model

Suppose we have a linear mixed model with outcome variable $Y_{ij}$ and covariate $X_{ij}$. In particular, suppose we have a random intercept model: $$\mathbb{E}[Y_{ij}|b_i, X_{ij}] = \beta_0+b_i+ ...
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1answer
13 views

Representing confidence ratings on choices as a variable or as part of the choice alternative in Mixed Logit Simulation

I am estimating a mixed logit model with hierarchical Bayes procedures to deal with my categorical data. I am wondering if I'm representing the data correctly. The data comes from experiments where ...
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1answer
36 views

Pre-post treatment design: accounting for reduced effect of treatment in baseline high scorers

I'm planning a study in which I want to test the effect of a treatment on a dependent psychometric variable. I expect subjects who score lower at baseline to benefit more from the treatment (larger ...
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1answer
92 views

Interactions between random effects

I'm considering a mixed-effects model to try to understand factors that influence the number of ticks sampled on wild rodents. My data is nested so that I have one tick count per rodent, multiple ...