"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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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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19 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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28 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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41 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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47 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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32 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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26 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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16 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
29 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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Linear mixed effects model using lme (repeated observations over time)

I'm trying to understand an lme() snippet I was given to interpret a particular data set, but am having difficulty understanding what it actually means. The data ...
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1answer
38 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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41 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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14 views

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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46 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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21 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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13 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
73 views

anova type III test GLMER wiht R

I am fitting a GLMER with lmer R package. I'm looking for an anova table with p-value shown therein, but I cannot find any package that fits it. Is it possible to do it in R? The model I am fitting ...
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1answer
27 views

Fitted values of 'lme' function result

I fitted a linear mixed model with R as follows. ...
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1answer
42 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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20 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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27 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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62 views

Multiple comparisons with interactions of mixed lmer model and how to report them

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 months, 4 months, ... etc. I test ...
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1answer
151 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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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
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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
67 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
98 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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31 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
12 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
29 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
68 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 ...
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1answer
36 views

Nonlinear model wirh effects over linear term

I have been working in R with nonlinear models such us: $Y = \alpha_{0}\text{(varia)} + \alpha_{1}\text{Time}\text{(varia)} + ...
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24 views

How to fit a random effect for only a subset of the observations (using R)

Say we have the following model: $$Y_i = \alpha + u_{j(i)} + \epsilon_i$$ for $i=1,\ldots,m$, for some groups $j=1,\ldots,J$, and $$Y_i = \alpha + \epsilon_i$$ for $i=m+1,\ldots,n$, where ...
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Is my dataset suitable for a mixed effects model?

I've been putting a lot of work over the last few days into bring mixed effects models to bear on some behavioural data I've collected for my thesis, but it's occurred to me that I'm not 100% sure ...
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277 views

How to get the overall effect for linear mixed model in lme4 in r?

I would like to get the significant value and effect size of the independent variable in overall, rather than the normal output from lme4 in R. It is just like the thing people report when running ...
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44 views

Plotting fitted values for an nlme model

I just got the output of my lme (nlme) model called shalit5 with syntax: ...
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1answer
35 views

Residual structure in Linear Mixed Models with Random effects

You can further improve a linear mixed model with random intercept and slope by specifying a structure in the residuals (for example AR(1)). In SAS it is possible, but I hope this is also already ...
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48 views

Identifiability in nonlinear mixed-effects models

I am interested in the identifiability of linear mixed effects models. Let's assume $p$ subject are observed at different instants in time. Let $\mathbf{y}_{i}$ $(1 \leq i \leq p)$ the vector ...
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27 views

Subjects:condition interaction random effect in a growth model

I'm investigating the effect of 'Condition' (3 levels: Quiet, Intelligible, Unintelligible) on pupil response over time (intercept, linear, cubic, quadratic, quartic and quintic terms). When I use ...
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1answer
587 views

lme4: glmer problems with offset()

this is my first post, so I hope everything is in the right format. I have some problems with glmer and don't know how to fix it, so I hope somebody can help me out with this. I could not find an ...
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1answer
58 views

Repeated measures mixed modeling. Why is Time (day, second etc.) a fixed effect?

Let's say I have an experiment where I repeatedly measure something over Time (1:10), say 10 days. Here I simulate some data... ...
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Correlation of fixed effects with multiple response variables in MCMCglmm

I'm working with a mixed model for which I have several response measurements for every individual. One goal is to determine the sampling variance/covariance of the fixed effect estimates for a ...
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21 views

Adjusting data for measurement errors

I have approximately 500,000 data points that were mechanically measured over about 2000 days. The equipment is manually set up each day, which likely induces some error. What I am attempting to do ...
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39 views

calculate VIF for glmm

If we have colinearity among our axplanatory variables we can calculate a varianvce inflation factor to estimate the effects on our standard errors $$ VIF = 1/(1-R^2) $$ I am unsure how to calcuate ...
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305 views

Trouble finding good model fit for count data with mixed effects - ZINB or something else?

I have a very small data set on solitary bee abundance that I am having trouble analysing. It’s count data, and almost all the counts are in one treatment with most of the zeroes in the other ...
2
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1answer
382 views

Calculate log-likelihood “by hand” for generalized nonlinear least squares regression (nlme)

I'm trying to calculate the log-likelihood for a generalized nonlinear least squares regression for the function $f(x)=\frac{\beta_1}{(1+\frac x\beta_2)^{\beta_3}}$ optimized by the ...
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64 views

Multivariate multi-level analysis in nlme

The question I have a dataset which I think requires a multivariate multilevel analysis. I am unsure both of the appropriate model and of how to fit it with R. I ...
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1answer
289 views

Negative values for AIC in General Mixed Model

I'm trying to select the best model by the AIC in the General Mixed Model test. The best model is the model with the lowest AIC, but all my AIC's are negative! So is the biggest negative AIC the ...