Tagged Questions

"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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How to report mixed effects logistic regression

I have several models predicting different binary outcomes as a function of time (binary variable: before/after intervention) and age (ranges 4 to 14), measured in different students within different ...
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6 views

Proc Mixed for a random slopes model - contrast the slopes?

I have a need to make predictions about a set of students $^1$ who are nested under teachers, under schools, under districts. I have produced the below model, and I now wish to do some forecasting at ...
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35 views

Using the same variable as a fixed and random effect in Mixed Effect Models

The experiment this data comes from an experiment where two people collaborate to put objects in a specific order. The Direction has the target array on their screen, and the Matcher has a scrambled ...
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1answer
56 views

Interpreting a linear mixed effect model's interaction term

I am a biologist and am attempting to analyze the effects of time and location on depth. I was told I needed to use a mixed effects model to account for the random variables of Individual and tracking ...
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30 views

Trying to understand the basics of a mixed-effects logistic regression model for a 10-step continuum

I am trying understand how to correctly build a mixed-effects logistic regression model in R. I believe my model is pretty simple and straight forward but I'm lacking in experience and uncertain I'm ...
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1answer
30 views

Fixed effect vs random effect when all possibilities are included in a mixed effects model

In a mixed effects model the recommendation is to use a fixed effect to estimate a parameter if all possible levels are included (e.g., both males and females). It is further recommended to use a ...
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28 views

Mixed effects structure: Main effects in random slopes with between-subjects design

My question is about whether it is appropriate to include certain random slopes in a mixed effects model with a between-subjects design. This is my first question on this stack exchange, and I'm ...
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1answer
64 views

One observation per level in mixed-effect model

Field explains how to analyse repeated-measures data using linear mixed-effect models (LME). See Field et al., Discovering Statistics Using R, 2012, p. 573. However, the way he specifies the model, ...
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20 views

how to fit nlmer non-linear mixed model and have asymptote fixed?

I'm trying to compare the model where asymptote value varies over subject and the one that does not. I've fit the first (the one that varies) but can't seem to figure out the latter. The first one is ...
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1answer
41 views

What statistical test is performed by summary(glht(model, linfct=mcp(factor=“Tukey”)), test=adjusted(type=“none”))?

I have data that I have fit using lme with the following structure (Subject is implemented as a random effect in order to account for multiple paired comparisons): ...
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11 views

Compare linear mixed models with Likelihood ratio tests and significant fixed effects

I am comparing two models with likelihood ratio tests and I have found the -2LL increases with the more complex model (when a 3-way interaction between 3 fixed effects is included). However, the tests ...
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31 views

How can I model this problem?

Genetic algorithms are a kind of evolutive approach to problem solving where solutions are randomly generated and crossed with each other as to produce other solutions. With each generation or ...
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16 views

Adding a variance structure when fitting a gamm with Gamma distribution

I am using the code below to fit a gamma GAMM introducing a variance structure that informs the model that variance of the response variable is much larger in one of the levels of the factor coast ...
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1answer
53 views

F stats for post hoc test of a linear mixed effects model

I have an unbalanced linear mixed effects model with three fixed factors of various levels and one random factor for my repeated measures data (for details see here). Thanks to your help I managed to ...
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1answer
14 views

Measurements from two raters. Should I use multilevel/“random-effects” model?

I have several variables that were measured on patients, for most patients the variables of interest were measured by 2 independent "raters". Most of the variables are binary. I need to compute the ...
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0answers
41 views

Accounting for heteroskedasticity in lme linear mixed model?

I have a data set where I measured the number of molecules (M) present in cells as a function of drug (with or without) and days of treatment (5 timepoints). I repeated the experiment 3 times, with ...
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58 views

time varying continuous covariate with one single binary outcome

Despite having only a single binary outcome for each ID, there are multiple correlated measurements for the same test for each ID at different timepoints. The individual ID´s are obviously ...
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226 views

How trustworthy are the confidence intervals for lmer objects through effects package?

Effects package provides a very fast and convenient way for plotting linear mixed effect model results obtained through lme4 ...
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11 views

Two repeated measures treatment analysis. Regression of the delta or mixed effect model?

We want to study the effect of a certain treatment on performance on a test and I would like to have some suggestion from you. We want to use a regression model in order to control for confounders. ...
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2answers
51 views

Comparing between random effects structures in a linear mixed-effects model

During a recently asked question about linear mixed-effects models I was told that one should not compare between models with different random effects structures using likelihood ratio tests. Up until ...
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1answer
44 views

Mixed and random effect model with multiple crossed random effects in lme4 vs nlme

I am trying to fit a few models as follows for my data of observations recorded from $p$ genotypes planted in $n$ locations for $m$ years. The aim is to estimate BLUPs finally. $$Y_{ijk} = \mu + G_i ...
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2answers
62 views

How to report a linear mixed-effects model equation

I have run a linear mixed-effects model, with one fixed effect (dd) and a random slope and intercept term for individual (fInd) and would like to know how to report the results? In particular, I would ...
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26 views

Joint Models vs the 'usual' time-dependent Cox regression for time-varying predictors

I've got a methodological question, and no data set attached. Suppose I aim to fit a proportional hazards model (Cox) for survival data. I have multiple observations for each individual (data in long ...
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1answer
63 views

Testing whether random effects are normally distributed in R

I've been working on a GLMM in R and I see that an assumption of the test is that the random factor must be normally distributed (that is, unless you're using a package like ...
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2answers
91 views

REML or ML to compare two mixed effects models with differing fixed effects, but with the same random effect?

Background: Note: My dataset and r-code are included below text I wish to use AIC to compare two mixed effects models generated using the lme4 package in R. Each model has one fixed effect and one ...
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49 views

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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71 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
65 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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8 views

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
79 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
189 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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33 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
29 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
258 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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29 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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39 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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62 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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212 views

Mixed effect linear regression model output interpretation

I just fitted the following linear mixed effects model: ...
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1answer
94 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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13 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
50 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
103 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
49 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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44 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
72 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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87 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
163 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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170 views

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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68 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 ...