Questions tagged [mixed-model]
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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Determining dependency structure in a data set for GAMM
I collected species richness data along permanent transects over the course of 3 months. So observations were made at the exact same location, where each transect was sampled once a day for 12 days ...
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How do I move forward to find a better model fit, help interpreting DHARMa residuals
I am trying to test if there is an effect on number of individuals depending on the proportion of a certain land use type and its management. But I don't find a model with a good fit. There seems to ...
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lmer 0-intercept model with binary predictor: Get Cohen's d for difference from zero for both groups
I have a binary predictor group = c("negative", "positive") and this model syntax: ...
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In a mixed model: Is there any statistical problem of using a random variable that is highly corelated to my variable of response?
I would like first to mention that I am not statistician but I work with lineal mixed model and like to know more about statistic behind them.
Here my question:
I have a mixed model where I have ...
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Plotting random effects in mixed-effects model
I have tried reading the documentation in sjPlot but couldn't figure it out.
In a multilevel / hierarchical / mixed-effect model, ran with lme4 in R, the summary() output give an estimated variance ...
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Computing effect size (d) for lmer() in R
I have selected to compute the Cohen's d effect size for the fixed effects of my linear mixed model. However, it's a little unclear why I'm getting the results I am. First, I am using the method ...
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Best test to compare cell population counts across patient groups
Given a data frame structure similar to the following:
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Question about 2 way mixed ANOVA when there is a significant between-group effect and it's relations to my hypothesis
I'm doing a research project for university and am trying to figure out how I should be interpreting my between-group effect in my mixed ANOVA.
My within-subjects variable is time and my between-group ...
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PROC MIXED HELP [closed]
I am just starting out with PROC MIXED and unable to find help at my university, so hoping someone here can help!
I am setting up a model where my outcome (weight) is measured 3 times (baseline, 12m, ...
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How to specify a linear mixed model (LMM) for a repeated measures design with two categorical predictors and one continuous?
I would appreciate some help figuring whether a linear mixed model (LMM) is a good choice for my data.
My experiment is a 3 (neurostimulation target) X 2 (task block) repeated measures design that ...
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Linear mixed-effects models or one-hot encoding for grouped data
I wish to perform linear regression over a data set whose entries can be divided into two or more groups. The groups could be, for example, the date at which observations where taken, or the patient ...
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What is the difference between autocorrelated residuals and controlling for the previous time point in mixed effects models?
I have several dozen observations from about 100 people who participated in an ecological momentary assessment study. I am using mixed effects models to estimate the effect of $X_{t-1}$ on $Y$.
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Mixed effects model for prediction
I have a dataset where I collected cortisol samples 3 times a day, for 3 days at 2 timepoints. I am interested in looking at changes in cortisol right after awakening, at 0 min after awakening, 30 min ...
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Specifying a mixed effects model with repeated constructs but cross-sectional observations (crossed vs. nested data at three levels)
I have a question about specifying a mixed model with crossed data across multiple levels. Consider the following situation:
Let’s say I collected data on Americans’ perceptions about the importance ...
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How to test whether null effect of condition is due to ceiling effect?
I have data from an intervention study on math learning. Participants were assigned to four treatment conditions in a 2*2 between-participants design. Participants were tested before the intervention (...
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interactions between variables using Generalized Linear Mixed Model in SPSS
I want to study which factors have an effect on the hormone PTH. PTH is used as a dichotome variable and is our outcome variable, the dependent variable.
We're using generalized linear mixed models in ...
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Understanding residuals vs. fitted plot for a linear mixed model
I am modeling body mass (y var) according to indices of dysregulation for different physiologic systems (x vars). I did a likelihood ratio test, which supported using a linear mixed model, with a ...
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How to specify random slopes when random effects are nested or crossed
I'm trying to run a model which has 3 random effects. Its data on an animal species and the random effects are 'group', 'mother' and 'individual'. Individual should be nested within mother, and then ...
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Using an EM algorithm for a random parameters model with mixed data
Suppose $x_i \sim f(\theta,\nu_i)$ and $y_i \sim g(\tau,\theta,\nu_i)$ and $\nu_i \sim N(0,\sigma)$. Importantly, $f$ is smooth in $\theta$, but $g$ is not.
We have data on $x_i$, $y_i$ and the goal ...
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Evaluating a cross over design with a very strong carry-over effect
I'm wondering how to properly evaluate a trial which was performed using a cross-over design evaluating two instruction techniques. Group A is instructed by technique 1, Group B by technique 2, both ...
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Which test statistic to report for (G)LMMs with categorical variables with >2 levels and/or interactions?
When building a glmm model with a binary outcome variable in R using the lme4 package I usually use something like the following structure:
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Is logistic regression with random effects appropriate for my problem?
My problem is the following:
I have 1/0 "conversion" outcomes.
I have samples from three groups: people who speak russian, people who speak japanese, people who speak portuguese. i expect ...
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Which linear model should I use?
I have data collected from an experiment in which 24 subjects did the same task 4 times. So in total I have 96 data points. My research hypothesis is that there are always linear relationships between ...
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Mixed Models two continuous time-points
I'm using a mixed model to do a hypothesis test of an intervention effect (group: 0=control, 1=intervention) in an RCT with two time-points: Baseline plus follow-up 6 months after baseline. In ...
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How to account for time in linear mixed effects model?
I have data collected over a year in months Oct2021, Dec2021, Jan2022, April2022, July2022, Aug2022, Oct2022. Ultimately, I would like to understand how my response variable varies across time. I ...
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Can I do a multilevel analysis for my study?
Some details about my design can be found below:
There are 2 groups: Group 1 and Group 2.
There are different numbers of people in each group.
A pre/post (measurement) of stress is taken several ...
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Can you use linear regression to predict individua or group player performance from team performance in a Public Good Game?
I am doing an analysis of the experimental data I have collected. In particular, I should do a panel regression.
I have collected data from my experiment on public goods. My variable of interest is ...
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Is it bad to have large random effect variance when fixed effect estimates are small?
I'm running a generalized linear mixed models (GLMM) and am comparing the Laplace approximation to the Gauss-Hermite Quadrature. I have three predictor variables (fixed effects) and each is a number ...
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Linear Mixed Models for randomized clinical trial
I am working on analyzing data from a randomized clinical trial which is studying the effect of a mesh type on patient-reported pain. The 2 study arms are the 2 different meshes (biologic and ...
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Hypothesis testing with data which is both pair and repeated-measures
Suppose I conduct an experiment to test the hypothesis that treatment A suppresses protein X. I am fortunate in that I work on kidneys, which come in pairs, however I am unfortunate in that I don't ...
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Analyzing discrete Proportional Data with different sample sizes in GLMM?
I am reaching out to seek guidance regarding an issue that has been troubling me for a while.
In my study, I had participants choose a strategy for expressing 6 different emotions across * 5 social ...
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Why is lmer model correlation in R very different when switching the predictor and response variable?
I am using the lme4 package to create a linear mixed effects model that accounts for repeated measures.
Data
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Comparison of multilevel models via deviance test
I have a question regarding the comparison of the following two multilevel models:
Null model: outcome.nullmodel <- lmer(outcome ~ 1 + (1 | ID), data=multileveldata)
Random slopes model: outcome....
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How to tell if I'm pseudoreplicating in a mixed model by taking slices of the same measurement
Here is my data setup. The dependent variable is mean resultant length (MRL), i.e., in context, the degree to which a firing unit is firing in phase with a particular frequency of the local field ...
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Are my data independent?
If I wanted to analyze data taken of patients meeting pre-specified criteria from several hospitals through a linear regression (say how hypertension changes given age and sex), I think that a mixed/...
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AIC-BIC in mixed models
I was reading about mixed models and I am confused about AIC and BIC criteria. My first question is can I use this types to calculate them?
AIC=2d-2ln(l)
BIC=dln(n)-2ln(l)
where d: is the numbers of ...
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Get random effect value from pattern of data
Rasch models are typically fit through an item response theory framework, but can also be estimated through a mixed effects model (e.g., see here). This is highly useful in my case because of some of ...
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Likelihood ratio tests vs. ANOVA for interactions in linear mixed model
I am analyzing a longitudinal study where patients received either treatment 1, treatment 2 or no treatment (placebo) using linear mixed models (LMM) in R. I have a baseline measure that is related to ...
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Seeking Feedback on Mixed-Effects Model with Weighted Observations
I've been working on a project where I'm comparing different methods using a mixed-effects model, and I'd appreciate some feedback on my approach.
Background:
I have a dataset with several variables:
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Extremely small confidence intervals and standard deviations in a clmm-model
I have a data set with an effort rating (varying in an ordinal scale from 1 to 7) as the response variable and a time point of measure (seven consecutive measures) as a fixed factor. An individual is ...
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Are one-to-one levels structurally identifiable in a multilevel model?
I have three categorical variables $A$, $B$, and $C$ representing three different levels of spatial regions. Every element of the image of $C$ is a proper subregion of $B$, and likewise for $B$ in ...
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Seeking software recommendations for efficiently analyzing large 3-Level data with generalized mixed effect model
I am currently working on analyzing a substantial dataset using generalized mixed-effect models. The dataset has a 3-level structure: 400,000 individuals nested within 500 neighborhoods, which are ...
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When using a likelihood ratio test to test for significance of a main effect, should I use the most maximal or minimal model as a base model?
Lets suppose I have a set of n covariates, and I want to test for the significance of the main effect of covariate i. I want to do this using a likelihood ratio test; fitting a model with covariate i ...
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How to describe a repeated measures GLMM?
In this experiment cows were fed with two different types of grass (Treatment) and we measured the weight gain over time, keeping track of the individual's ID. Sex of the individual was also taken ...
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Proper analysis of completely crossed design with subjects and items as random effects (brms)
I have the following study design:
stimuli: 240 pictures:
6 pictures of 40 students each
(each student fixated one of six points and during each fixation one picture was taken)
each stimulus was ...
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How to show mathematically that random effects are more efficient than fixed effects?
I have read in several places now that random effects estimators are more efficient than fixed effects estimators, in particular here
I’ve searched this site and Google and couldn’t find this result. ...
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Nested data correction with mixed models
We have collected data from n patients, with each patient having one eye treated and the other untreated.
We would like to see if the treated eye progresses differently to the untreated eye using ...
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How to test if the relationship between a predictor and an outcome variable varies as a function of a within-subjects categorical variable?
I am designing a study that has the objective of assessing if working memory varies throughout the day (morning vs. afternoon). I will measure 5 components of working memory with 5 cognitive tasks. ...
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GAM posterior simulation for bird population trend
Background
This is a follow-up on my last post.
I have a GAM of presence of a bird species from a large dataset. There are over 400 sites in my data, where each site corresponds to a unique observer. ...
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