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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How to test the inclusion of a single random effect in glmer?

Suppose I have two models: m1=glm(DV~IVs) m2=glmer(DV~IVs+(1|Subject)) How can I test the inclusion of that random intercept in R? I know that I can't use ...
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Mixed-effect models for repeated measures - problems with the “Significance level”

I am trying to fit a linear mixed-effect model to my dataset to see the relationship between a self-reported questionnaire and some physiological data. I've created a first model including all the ...
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Interpreting results of a Linear Mixed effect Model

I am trying to implement a Linear Mixed-Effects Model in Matlab. I have many repeated measures of some features in a longitudinal data set of 51 people. I considered a random intercept that varies by ...
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ICC as expected correlation between two randomly drawn units that are in the same group

In multilevel modelling the intraclass correlation often gets calculated from a random-effects ANOVA $$ y_{ij} = \gamma_{00} + u_j + e_{ij} $$ where $u_j$ are the level-2 residuals and $e_{ij}$ are ...
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Difference between weighting and replicating observations in linear regression

I have a model in which each case is summary statistic of many observations. I am using a mixed effect model (lmer() in R) for prediction and I thought to give ...
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Fixed-effects variable selection for mixed-effects regression

Does anybody know if it is possible to apply some "feature selection" algorithm to a dataset prior to creating a mixed-effects regression model? I am trying to implement such a modelling in Matlab, ...
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Interpreting random slope for a dataset with missing data in mixed model

I am struggling to understand the meaning of random effect for the dataset with missing data based on mixed model, I am appreciated if anyone can help. Here is an example. let us say we have 20 ...
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Controlling for variables with lmer (R)

I am using lmer (from the lme4 R package) on a dataset with 6 variables: SubjectID, ImageID, Category, Brightness, Contrast and ResponseTime, where the last three are continuous variables. (and yes, ...
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In a mixed effects model, how do you determine when the slope and intercept should be independent?

This is a question regarding the theory underlying mixed effects models, specifically a general rule of thumb that can be used to determine the structure of random-effect portion. Here's what I ...
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Mixed-effects model: basic questions

I am trying to implement a mixed-effects regression model in Matlab to see the correlation between self-reported stress levels and some physiological features. Data comes from a longitudinal study so ...
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Random effects for second order in R mixed models

I am fitting a mixed effects model in R using nlme lme(y~x+I(x^2),random=~x|subject,data=train) Is this the correct way or should it be ...
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meta-analysis mixed model - polygons based on meta-regression

When using meta-regression with factor moderators, result differ a bit from using seperate estimation based on subgroup, even if the same model (mixed effects) is used for both. I understand the ...
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RJAGS bayesian approach of mixed effects model

Why my posterior result always shows that the sigma and sigma.c estimates to be around 50? It should not be that large as I know from another approach of analysis and also summary of the data. Is it ...
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robust mixed models 3 time points (y-side) and high dropout

I am running the model in R: model = rlmer(Tau ~ tract_FA_avg + (1|Subject), data=long2) (robust as I have outliers) Since I am relatively new to mixed ...
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Hierarchical, Linear mixed-effects model

The aim of my task is to ""investigate whether and how various factors affect the evolution of the life expectancy"". The data includes country, year (just a few and discontinuous like 1990 2007 2011, ...
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Heteroscedasticity and bias shown in residual plots, lme

I have been fitting a linear mixed-effect model. The residual plots are not desirable. I have found many posts telling me the first is heteroscedastic, and the second is biased. But I can't find info ...
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Nested mixed experimental design with crossed factors for laboratory validation procedure: how to model it?

I have been asked to analyze the following laboratory experiment: 14 donors’ red blood cell samples are typed for rare antigen-asset recognition by an automated procedure (machine), which returns a ...
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Are these diagnostic plots from lmer too far away from normal and showing heteroscedasticity?

I have read similar posts in this website to help me assess whether my diagnostic plots are too far away from normal and if they are showing heteroscedasticity (Interpretation of residuals vs fitted ...
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How can I test the interaction of a 3-level, within-subjects variable with a continuous variable in R?

I would be extremely grateful for some advice on how to correctly fit linear mixed effects models with my repeated measures design! In my experiment, subjects completed a task with 3 difficulty ...
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Mixed models: Is there any way we could decompose the estimate variations by covariates? [closed]

I modeled $Sales$ for year $t$ of firm $i$ in industry $j$ ($sales_{tij}$) as a function of an intercept ($\beta_{0}$) plus a residual or error term ($xi_{tij}$): \begin{align} {\rm sales}_{tij} ...
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Within- and between-person variance in an unconditional means model

Testing an unconditional means model following the procedure in Chapter 4 of Willett and Singer Applied Longitudinal Data Analysis using the nlme package in R. The model takes the form ...
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Comparing groups with linear-mixed models

I have a problem with a dataset resulting from the repeated measurements of a clinical index on different patients. Each patient has been classified into two groups according to the index decline two ...
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Expressing fixed effects in a mixed effects model with more than 2 levels of the grouping variable

I am reading through Chapter 3 of Willett and Singer Applied Longitudinal Data Analysis trying to apply it to my own data. Specifically I am wondering about how to express fixed effects in a ...
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What, if anything, is the relationship between random intercepts models and compound symmetry?

In the analysis of correlated data, you're often working with replicates where a worker does a task 2 or 20 times, or an individual is measured for blood pressure randomly over several times during ...
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33 views

Help with zero-inflated generalized linear mixed models with random factor in R

My study has a complicated design and I am not sure if I am modeling my zero-inflated data correctly. I have seed abundances and seedling abundances for 11 species. I have one main "treatment" with ...
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Analyzing pre/post (longitudinal) data using limma/lme4 with adjustment for continuous covariates

I’m analyzing Illumina 450K data of a study of following design Subject Group Time-point Class 1 Control Baseline 1 1 Control Follow-up 2 2 Control Baseline 1 2 Control Follow-up ...
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How do I covary out a time-variable covariate in a repeated measures analysis?

I'm trying to analyze a longitudinal data set looking at pre- vs post-treatment effects on a single dependent variable. The difficulty I'm running into is that subjects in the group being analyzed are ...
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Is there an equivalent to simple slopes analysis in mixed effects modeling?

Suppose I have a continuous DV, four predictor variables, and I run a backfitting algorithm (i.e., LMERConvenienceFunctions) to find the best fit for my data, and I get a list of significant ...
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What is a good general guideline for mixed effects model building?

Suppose I have a dependent variable and half a dozen possible predictors. This experiment is wholly exploratory. What would be the best approach to discover which predictors (and interactions between ...
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66 views

Mixed model or ANOVA on differences in pre-post design

I want to analyse the effect of different treatment types (control, treatment1, ..., treatment4) on the surface of specimens made of certain materials (...
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33 views

Can I run generalized linear mixed models using lme4 on very small sample sizes?

I am analyzing data (size/survival) of two groups of fish (Group1, Group2) mixed together in tanks with two different environmental variables applied at two levels to the tanks, e.g. ...
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Predictions from Poisson GLMM (lme4) lower compared to GLM

I am modelling visitor counts to a sample of sites in a forest in order to predict the number of visitors to the rest of the forest. My predictor variables are time of day (categorical), day of week ...
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What is the right mixed effects models for data that is both nested and not?

I have a dataset that includes nested observations as well as repeat observations that are not nested (I'm not sure this is the best way to describe it, but stay with me). Here are the specific ...
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Questions about mixed model design with repeated measures/nesting/incomplete design

I have data from a incomplete factorial experiment with repeated measures and potential nesting and am trying to figure out 1) the right way to design the mixed model to analyze the data, and 2) how ...
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ANOVA table for mixed (nested design) model in R

I am trying to get an ANOVA table for a mixed model in R with nested design fit with package lme4, function lmer() in R. When I ...
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Which statistical test should I use in my diary study of repeated measures when trying to establish within-person effects?

I am having real trouble analysing the data for my Psychology dissertation. I am investigating the effects of physical activity on psychological well-being both at the between-person level (i.e. ...
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Convert SAS syntax for mixed models for repeated measures in R

I want to attain a p-value in R using lme4 or nlme which has been obtained from mixed models (...
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Plots to illustrate results of linear mixed effect model - continued [migrated]

I'm trying to create a plot similar to the one found here: Plots to illustrate results of linear mixed effect model (for ease of reference, here is the code from that link: ...
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predict() including random effects in lmer lme4

I have the following linear mixed effects model: m01 <- lmer(man ~ year + (1|refID/stuID) + (1|country), data = hunt, weights = harv) I am trying to plot a ...
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Could some one please explain the difference between Decay, Lag and Adstock?

I'm working on creating a market mix model and read that it is necessary to create additional variables to account for the lag and decay/adstock effect. Could someone explain how to create those ...
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Mixed model: Converting SPSS syntax to STATA [closed]

I'm currently using SPSS to produce a linear mixed-model for my study: Participants are divided into 2 groups, where each participant is tested over 3 days, with each day consisting of 12 blocks, and ...
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Nested fixed effects?

I have a question about an analysis that I thought would be really simple, but turned out to be a bit more complicated (or maybe I am just overcomplicating it/ my stats skills are insufficient, that's ...
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Check coding for repeated measures mixed model in lme4 and nlme in R

I have made some models in nlme and lme4 and want to check I have coded them right, because I need to account for repeated measures from each territory (one measurement in each season). I'm looking ...
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modeling sequential decisions

I am trying to model a 3 sequential decision. In my data context, there are two stores A and B. A consumer first decide to choose a store either A or B to visit, and then he decide to purchase a ...
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Nesting mixed effects ANOVA degrees of freedom

Consider the following dataset: ...
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Cook's distance in detecting outliers

According to my understanding, Cook's distance measures the influence of each observation by excluding points when fitting a model. So I assume it could be an reasonable approach for outlier ...
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32 views

How to fit a mixed effect model to a left skewed continuous response

Does anyone have any suggestions (short of transforming my data) on how to fit a mixed effect model to a continuous response variable that is left-skewed? Other words, what probability density ...
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When are zero-correlation mixed models theoretically sound?

The block quotation below, from leaders in the field of mixed effect modeling, claims that coordinate shifts in models with zero correlation between random effects ('ZCP' models) changes model ...
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Fixed Effect, Random Effect vs. Mixed effect and distribution assumption

From my econometrics class, we have learned that the difference between fixed effect and random effect is the assumption on the unobserved heterogeneity of the group. If one were to use random effect, ...
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Classification with non-independent, structured, data

My dataset consists of N subjects with two labels (A/B) and p features each. My goal is to train a classifier using data from (N-1) subjects on AvsB (e.g. Logistic Regression, SVM, etc), and test on ...