"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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What could be causing vertical trends in residual plots?

I'm fitting a mixed effects growth model and after fitting the model with a simple covariate term and random effect I get the following residuals: If I add in a quadratic term, I'm able to remove ...
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14 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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15 views

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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23 views

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 ...
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12 views

Intra-individual covariance matrix in lme4

I wonder, why do not need to specify the structure of the variance covariance matrix and the lmer function library lme4, since using the lm function library nlme this is possible. Thank you.
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1answer
21 views

correlated variables as fixed effect in mixed effect models

I am interested to know whether the count of beetles depends more on precipitation or in minimum temperature in winter. I currently model as fixed effects: altitude (correlated with temperature) ...
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15 views

Should I include weights in LME?

I have two case studies where I am looking at the influence of a trait (trait A) on mortality (m) of trees and seedlings. Following your comments on ...
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6 views

How to analyse interbirth interval data with 0s

OK.. So to give a bit of context, this is what my data looks like: My question is regarding the last variable column (IBI). This records the interbirth interval in days between each birth (the date ...
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1answer
31 views

Mixed models and longitudinal studies: Is it ok to specify a random slope with time as a categorical?

My model is currently setup as follows either with just random intercepts: ...
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17 views

Variance component model for longitudinal data

I have a dataset with fixed and random effects, sampled over time (body phenotypes under fixed stimulations). Generally speaking, I'd like to construct a variance component/ partitioning model to ...
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2answers
67 views

When the dependent variable and random effects 'overlap' in mixed effects models

I have added a new example here for clarity, see original question below Eg. I have 10 schools in 5 countries, ten students from each school is sampled. Prediction variables: student test marks for ...
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30 views

Post-hoc testing in multcomp::glht for mixed-effects models (lme4) with interactions

I am new to CrossValidated, so if there is a better way for me to format or ask my question, please feel free to comment. I am performing post-hoc tests on a linear mixed-effects model in R (package ...
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59 views

95% CI in nonlinear mixed-effect model {lme4} with two or more crossed random effects

I have fisheries-independent data and am interesting in estimating maturity patterns across 50 lakes that are sampled (with bias) by 4 types of gear-collections. The sampling pattern is very ...
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1answer
40 views

Nested linear mixed-effects model

I have 9 sites. Within each site, plant life was sampled to represent 70% of the basal area. Of the sampled plants, I know the corresponding family, genus, and species. For this project, I extracted ...
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37 views

Negative binomial mixed effect model for repeated measures with R - prediction and plotting

I have a dataset to analyze in which a response was recorded at the ends of months 1,3,4,5,6 in 187 patients. All patients had the responses recorded in each week, and all patients started a treatment ...
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1answer
15 views

Nesting v. interaction in LMM

I have a continuous response variable, a continuous predictor (P1) and a variable (elevation, P2) that could be treated either as continuous or categorical (I guess?). I also have an ID as the random ...
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1answer
126 views

Mixed-effect model design with a sampling variable

I am trying to specify a formula for a linear mixed effect model (with lme4) for my experimental design, but I'm not sure I'm doing it right. The design: basically ...
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1answer
44 views

Hypothesis testing: If not a p-value in mixed effect models, then what?

I've been working on a messy, repeated measures data set of endocrine data looking at a small group of variables (after eliminating several uninteresting contenders in exploratory data analysis), each ...
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2answers
50 views

Large differences between raw (plotted) data and least-squares means from mixed model

I’m analysing data with mixed-models (using the afex package which I believe is based on lme4) from an experiment that had a ...
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31 views

How to model time-series data with nested random and fixed effects?

I'm analysing PAM fluorescence data from an experimental set-up that I duplicated from an earlier experiment with a missing control. That's why I haven't given the statistics of the experiment much ...
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1answer
20 views

Post Hoc Analysis in Mixed linear models

I tested whether different version-styles of a loading screen (hourglass vs. progress bar) in different progression patterns (linear, accelerate, decelerate, irregular, binary) affect time estimations ...
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65 views

Pooled OLS, fixed, random or mixed effects?

I am analysing a simple balanced panel data with the following variables: ...
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91 views

R lmerTest and Tests of Multiple Random Effects

I'm curious about how lmerTest package in R, specifically the "rand" function, handles tests of random effects. Consider the example from the lmerTest pdf on CRAN that uses the built in "carrots" ...
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1answer
86 views

Examining trends with interactions and with stratification - obtaining discordant results

I'm examining the effect of income (categorized into quintiles) on a response variable during different years (from 2003 to 2014). I adjust for some other covariates and have repeated measurements on ...
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30 views

Treatment of mixed effect models for Box-Cox transformation

To analyse the Box-Cox transformation in a mixed effect model, no simple transformation/ code in R exists. So which of the following approaches would be valid ways and why? 1) Take a random sample ...
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37 views

How do I fit a linear mixed model in R with autocorrelation, when the effect of time is of no interest?

I am attempting to fit a linear mixed model with the lme function using R. My data involve repeated measures, but the effect of time is not of interest to me, so I don't want to include it as a fixed ...
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1answer
36 views

Material difference between Mixed Effects Model and normal Linear Model

I have a question about normal linear models vs mixed models. Say I'm predicting prices for certain products, and I know two things: store and brand: In a linear model (lm), this would be: ...
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25 views

Is there a more efficient way to partition my data for use in lme4?

I'm currently using lme4 to fit the following model: Model = lmer(CA ~ P + T + S + (1 | Study), Data) P and T refer to pressure and temperature, and there is an ...
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45 views

Study on both hands of patients, mixed effects?

We want to test the correlation of a certain surgical procedure on the hand (carpal tunnel) and the development of trigger digit. We have both hands of the patients, some hands underwent surgery, ...
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36 views

Striping in residuals for linear mixed effect models

I am looking at the effects role has an opportunities to collaborate between groups in a social network. At a basic level the data are modeled as: relRatio~role ...
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33 views

What does the dfbeta mean for an lmer regression?

According to the documentation: DFBETAS (standardized difference of the beta) is a measure that standardizes the absolute difference in parameter estimates between a (mixed effects) regression ...
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24 views

Heavy-tailed errors in mixed-effects model

I'm relatively new to statistical modelling and `R', so please let me know If I should provide any further information/plots. I did originally post this question here, but unfortunately have not ...
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31 views

In the optimal model, do I need to change 'REML=FALSE' to 'REML=TRUE'?

I did the model comparison using these three models: ...
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2answers
39 views

How do I identify a particular residual from a mixed-effects model in R?

Here's a plot of my residuals from a mixed-effects model in R (using lme4). There's one 'outlying' residual with a value of around 35 (index circa 90) that seems anomalous. I don't know if it has ...
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1answer
25 views

Random variable in mixed-effect model (ecological studie)

I'm beginner with the mixed-effects model, so I already apologize if my question is a bit naive. My problem is the following : I sample each time 30 plants in 6 populations on 9 mountains. So I ...
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1answer
83 views

Should I include this fixed effect? lme4 likelihood ratio test and lmerTest anova disagree

I have a mixed-effects model with two fixed effects and one random effect (group membership) estimated using lme4. log_dv ~ iv1 + iv2 + (1 | group) I want to ...
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1answer
31 views

power for mixed-effects model

I wonder if there is a simple way of calculating an achieved power for a mixed-effects model. The fixed effects are the intercept and a slope. The random effect is for the intercept at the two levels ...
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19 views

Which is the difference between conventional 2-way repeated measures ANOVA and mixed effect ANOVA?

Assuming I have two within-subjects factors (Xw1 and Xw2) for my experimental design I can therefore perform two way repeated measures ANOVA using the conventional procedure in R ...
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1answer
67 views

Real motivation for using mixed effect models, and when to use them and when not to

My question might sound naïve, but despite my internet search, I wasn't able to find a satisfactory answer. I've been introduced to linear regression, linear fixed effect and linear mixed effect ...
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1answer
41 views

What is the nature of the normality assumption in models for longitudinal data?

I'm working on a longitudinal dataset to which I've been fitting non-linear mixed effects model in R. Regarding normality, I have a few questions: Can I assume that a longitudinal data is normally ...
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1answer
29 views

Mixed-effects model without the random effect in the design?

Is it appropriate to create a mixed-effects model (for example, using SAS Proc Mixed) that specifies a random effect but does not include the random effect in the model itself? I ask because it seems ...
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1answer
40 views

Intercept in random effects mixed model no longer significant

When I add a categorical fixed effect to my mixed model (with one random effect and three continuous fixed effects) the intercept is no longer statistically significant. Does this mean that the newly ...
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1answer
461 views

Obtaining adjusted (predicted) proportions with lme4 - using the glmer-function

I aim to estimate the annual proportion of patients (% of patients) that are smokers in a population whose age and sex must be taken into account. In other words, I want to calculate the adjusted ...
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1answer
50 views

Why are the beta values provided in lmer() different than simple group means of observations?

In a 2-level mixed-effect model, the equation for level-1 is $$Y_{ij} = \beta_{0j} + r_{ij}$$ where $\beta_{0j}$ is the mean outcome for the $j$-th group. I ran the following model: ...
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1answer
114 views

R-Metafor: Meta-analysis and mixed effect model

This is an example of my dataset ...
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1answer
74 views

Post-tests to consider in mixed models

I have a mixed model of the form y~condition + Replicate + Error(Replicate) but at the moment, and am running into difficulties in performing a post-hoc test. I ...
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19 views

Mixed effect linear model R

Could someone please help me with interpretation of the results I've got using nlme package from R. I have 3 groups of animals, each group is divided into 3 subgroups, and each subgroup has a number ...
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0answers
39 views

What happens when fixed and random effects overlap?

For example, if your response is the number of ticks on deer, and you sample deer at 10 sites. You include 'site' as a random effect, but you also want to include the density of trees at each site as ...
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21 views

How to analyse the ratio of two continuous variables sampled repeatedly over time

I am measuring reproductive hormones in dolphins over time to look at seasonal changes. The sample type (respiratory vapour) that I am using suffers from variable water dilution that cannot easily be ...
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13 views

Calculate elasticities of mixed logit

How do we calculate the dis-aggregate direct elasticity of a random-coefficient logit model?