# Tagged Questions

Mixed (aka multilevel or hierarchical) models are linear models that include both fixed effects and random effects. They are used to model longitudinal or nested data.

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### Interpretation of glmmPQL() spatial autocorrelation output

I am modeling binominal data with random effects and spatial autocorrelation using MASS::glmmPQL(). Plotting the residual semivariogram of a model fit without ...
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### Levels of a categorical variable in Wilkinson-Rogers notation without intercept

I would like some clarification regarding a regression specified using Wilkinson-Rogers notation to produce coefficients for all levels in a categorical variable. Consider the regression specifed by <...
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I have drawing data from 10 subjects drawing 8 shapes (and many repetitions of every shape). I fitted a model to this data Matlab, separately for each subject and each shapes, such that I have 2 model-...
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### Random effects negative binomial model in Stata

I am running a random effects negative binomial model for count data. Patients were randomized to 3 treatment groups and were seen over varying number of visits (time) i.e. the data is not balanced. ...
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### Manova, mixed models or what?

I have difficulties in choosing the appropriate statistics to use for my data. In particular I don't know whether I have to use a MANOVA or a mixed model. Let's suppose, I have three dependent ...
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### Simulation of random-effects meta-analysis yields biased tau^2

I need to realistically simulate study effect sizes and within-study variances for a random-effects meta-analysis in which the outcome is a relative risk. My question: why does this simulation lead to ...
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### mixed noise and gaussian

I have a large number of data sets. Each data set has something 200K data points lying in a square times a circle. The square is solid $I\times I$. The circle $S^1$ is hollow (dim 1). By reasoning ...
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### Extract the different components of variance in a linear mixed model in R

Consider a mixed model as follows. ...
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### Nested random factor with confounding (random?) variable

I have a question on how to specify a GLMM. I made an experiment with two treatments (control and treated) to test the effect of a water contaminant on reproductive cells of tadpoles. I have data on ...
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### Cumulative link model with categorical or continuous predictors?

I have data in a perception experiment where I show surfaces slanted at different angles and ask participants to judge whether the surface could be stood on. I also asked them how certain they are ...
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### Analysis of variability for independent variables

I have dataset of four urinary markers collected over a period of 10 years.All these markers are independent of each other. The hypothesis is there is no difference in values for each marker collected ...
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### I want to check the “affect of economic variables on the export of vegetable ” [on hold]

I have used ARDL technique for that as I applied that technique following answer come to me. Value of Durbin Watson test (2.20). Please guide me how i can interpret that value?? In the long run ...
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### How to include nested fixed effects with different levels across conditions in lmer?

My design is as follows: 1. one dependent variable (brain activity), 2. a "condition" factor I manipulated with two levels (c1 and c2) 3. a "region of interest" factor with two levels (r1 and r2) *...
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### Variance of Linear Combination of Fixed Effects in Mixed ANOVA Model

Consider the mixed effects model described here. It suffices to consider only the balanced case. I need to make inference about the linear combinations of the fixed effects $L = \sum_i c_i \tau_i$ I ...
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### Estimate of Fixed Effect in Mixed Effects ANOVA (Restricted versus Unrestricted)

Consider the mixed effects ANOVA model described here It is stated that the estimate of the fixed effect is $\hat{\tau}_i = \bar{y}_{i..}-\bar{y}_{...}$. But is this true for both the unrestricted ...
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### Confidence intervals for odds ratio in GLMM with interactions

I have the following output from a GLMM The model is  \log\left(\dfrac{p_{i}}{1 - p_{i}}\right) = \beta_0 + \beta_1 \texttt{type}_i + \beta_2\texttt{treat}_i + \beta_3(\texttt{type}\times\texttt{...
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### How to model GEE (generalized estimating equation) in data coming from two datasets?

I would like to model X (sentiment score, continuous between -1 and 1) and Y (smoking status, either 0 or 1). Individuals can be clustered by the "State" variable. It would be the most ideal if I ...
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### Unbalanced linear mixed effect modeling for longitudinal data with lme4

I'm new to longitudinal analyses, and I'm having trouble formulating a model that accurately reflects my study design. This study recruited subjects for two groups (dx vs. control), with measurements ...
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### Hierarchical regression model with just 2 populations

I have a dataset with the scores in Mathematics of students coming from 2 different schools. I'm trying to implement a hierarchical linear model to predict the student score given a set of covariates. ...
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### What could be the reason for a coefficient's change in magnitute and/or sign for identical specifications of OLS and Random Intercept Models?

What could be the reason(s) for a coefficient's change in magnitute and/or sign for identical specifications of OLS and Random Intercept Models? Further, does the Random Intercept Model, controlling ...
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### Should I use a mixed-effects model?. Measures at different locations in several pieces

Imagine a simple experiment: I have 10 "almost identical" pieces. I take the first one and I measure the temperature at 5 different distances from its center. I take the second one and I do the same ...
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### Fitting and interpreting random effects in repeated measures and unbalanced ecological data set

I have a vegetation data set that consists of 150 plots that were sampled 1-3 times over a three year period. Plots are my unit of observation and they are unbalanced (since plots were sampled either ...
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### Multilevel meta-analysis with non-independent effect sizes: correct model?

I'm conducting a meta-analysis on standardised mean difference scores. Some studies provide multiple effect sizes, thereby violating the assumption of independence. An example is given below (all ...
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### Finding differences between groups with linear mixed model

I am trying to analyse how a measured variable differs between groups and time. My data has such structure: ...
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### Use of Weights in Linear Mixed Models to improve error structure instead of transforming the Dependent Variable

I am runnning a Random Coefficient Mixed Model in R using lme in {lme4}. I had to transform ...
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### Model design and nonconvergence problem with GLMM, incomplete block design in R

I have a two-part question that includes issues with generalized linear mixed models and failure to converge. First, a little bit about my experimental design. I have data where I am trying to test ...
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### Variance component analysis on marginally penalized LMEs

I have a series of nested LME's, each tier of which has been marginally penalized using elastic net (lassop function in {MMS} R). I'm very interested in looking at shifts in variance component ...
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### permutation testing and mixed effects models

I am rather new to both permutation tests and mixed effects models, so forgive me if this is a ridiculous question. I would like to run a permutation test for a model that has a random effect, ...