Questions tagged [multilevel-analysis]

Statistical analysis of datasets comprising several levels of hierarchy (e.g., students nested in classes nested in schools or hierarchical forecasting). For questions about mixed models use [mixed-model] tag. For nested random effects, use [nested-data].

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How to perform multilevel regression on Y?

We know multiple linear regression has the equation $$ Y_1 = \beta_0 + \beta_1x_{11} + ... + \beta_k x_{1k} + \epsilon_1 \\ Y_2 = \beta_0 + \beta_1x_{21} + ... + \beta_k x_{2k} + \epsilon_2 \\ \dots \...
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Inclusion of time-related variable in longitudinal mixed model

I will use the sleepstudy dataset from the lme4 package to illustrate my question. In that dataset, the Reaction time of individual Subjects was measured each Day. Subjects were sleep deprived so as ...
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Very different sizes of parameter estimates in lmer vs glmer (binomial) versions of “same” model (R)

In a 2-level glmer analysis the assumptions did not hold, so I created a binary outcome variable instead and run the same model setup on that (most Y values were 0’s and 1’s originally). With regards ...
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Power analysis and sample size for multilevel modeling growth curve (repeated measures)

I am aware that there are some useful threads already on free software for calculating sample sizes (see here). However I couldn't find anything specific to cross-classified MLM and repeated measures. ...
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Bayesian Model selection vs Model comparison

Is anyone aware of any articles or book chapters about the distinction between model selection and model comparison in bayesian multilevel modeling? I am fitting several competing growth models using ...
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separate models vs joint model

My goal is to estimate the association between children BMI and distance to the nearest fast food restaurants. The hypothesis is that children BMI increases with increasing proximity of fast food ...
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What happens to the Correlation coefficient for a multilevel random intercept regression?

Suppose we have a two level random intercept regression model: that is, for i = 1,...n, $$X_{i} \sim N(\mu_{xi}, \sigma_{xi}) $$ and $$Y_{i} \sim N(\mu_{yi}, \sigma_{yi}) $$ where $$\mu_{yi} = a_{i} +...
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Is the term “latent effect” in statistics has the same meaning as “latent variable”?

Is the term “latent effect” in statistics has the same meaning as “latent variable”? If not, then what would be its substantive interpretation? UPDATE: There is a whole class of models called “Latent ...
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Multilevel/ Mixed Model / HLM Centering Interactions Level 1 and Level 2 Cross-Level

I am having some trouble with the literature on the correct model specification for my question. Here is the setup: I have a multilevel model with a variety of variables at level 1 and a single level ...
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How do I specify which variables are at which levels in a hierarchical linear model?

A reviewer has suggested I do a hierarchical linear model for a journal article, but none of the tutorials I could find online: (Example: 1, 2, 3, 4...) were helpful. I want to construct a ...
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How to test for differences between groups in EEG trial data?

Experiment Setup Each participant must perform volutary biceps flexions (each flexion is referred to as a trial $t_i$) while staring at a screen. EEG and EMG signals are recorded throughout the ...
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Models fitting to different data but input is the same [closed]

I am currently running candidates for a meta-analysis using the rma.mv function in metafor. I have tried running models, comparing by AIC, and then averaging using the model.avg approach in the MuMIn ...
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categorical predictor in lmer appears to give reverse direction from same linear model without random effects

I'm running a mixed effects regression using lmer and getting a result that concerns me. The colleagues I'm working with are sceptical of mixed effect models (and control variables), and although we ...
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I am testing growth in 4 different hydrogels (and in 4 different medias). Which test should I use to determine which hydrogel was best overall?

I am testing in vitro ovarian follicle growth in 4 different hydrogels. I have also tested 4 different medias with each hydrogel. I need to use a statistical test to determine which hydrogel was best ...
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Using multilevel modeling to test differences in the ability of trait and state measures to predict outcomes

I'm currently trying to test whether trait is better at predicting overall/mean job performance than state anxiety and whether state anxiety is better at predicting daily job performance than trait ...
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How to distinguish between measurement error and within-person variability in multilevel modeling/HLM

I'm currently running a model to determine if people vary in their daily levels of variable Y, and if daily levels of variable X predict daily levels of variable Y. I collected measurements of both X ...
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Correlations in a Multilevel Model

I'm currently running a daily diary study, where participants first complete a baseline survey and then complete the same survey each day for 10 days. My data has a nested structure (days nested ...
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Would a multilevel model (random effects) suit better

I have a question about whether multilevel modeling is appropriate in my situation. I’m working on an analysis looking at the effect of an training camp for factory workers in 20 different factories ...
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Multi-level mixed effects model - intercept insignificant

I am running a multi-level model in R, and the results suggest that the intercept is highly non-significant p = 0.9, but that two of the variables are significant. All the variables are Likert scores ...
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Gradient Descent for Multi-Level / Mixed / Hierarchical Regression Model

How would gradient descent work in a multilevel regression setting? This is fairly clear to me in a standard linear regression formulation, but haven't been able to wrap my head around parameter ...
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Does it make sense for a hierarchical regression model to use the same top-level factor in more than one hierarchy?

I’m creating a hierarchical model to predict student course grades in a given term based on a combination of student, course, and instructor characteristics. I'd also like to make inferences about ...
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how to use graph_model in reghelper correctly

I spent so many hours trying to create bargraph for lmer in R but I cant find a way to get each condition group mean to vary. I want to plot the following model ...
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Is my LMER model doing what I want? (Adding between AND within-Subject Variables)

My DV: COP (continuous) My IVs: Velocity (continuous, 15 distinct values, which are repeated for each participant) Rating (continuous, assigned to each of the velocity values, for each participant) ...
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Comparing Proportions Grouped by State of Residence

I am looking at whether one racial group has disproportionately low rates of a medical procedure compared to the racial makeup of their state - across all 50 states. My dataset has the state the ...
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Estimation of random intercept and random slope for singleton cluster in multilevel modeling

I am performing some multilevel analyses with the R package lme4. The study design is longitudinal with the hierachical structure of observations (L1) nested into study participants (L2). I have 215 ...
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Three-tier Multi-Level Model: violation of the assumptions of normality and heteroscedasticity

I am working with educational data. To do so, I am using the classic three-level hierarchical linear model (student, class and school). I am using the R software lmer package and the stata software. ...
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Multilevel modelling for multiple comparisons - is my emmeans implementation correct?

I've run an experiment with several conditions and would like to analyze bernoulli outcome differences with a Bayesian multi-level model. Specifically, I am interested in average marginal effects (aka ...
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How to interpret the standard deviation of the slope random effect in a multilevel model

How do you interpret the standard deviation of the slope random effect in multilevel models? Suppose I want to show how Urbanization percentage changed across time in Western and Eastern Europe, so it ...
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Multilevel cross correlation - cross correlate time series nested in participants

I have observed behavioral and questionnaire data for 45 participants over a certain span of time. Now I'd like to find out which point in time of behavioral data best predicts questionnaire data. I ...
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R: Inflated degrees of freedom in mixed linear model

I have a question regarding a mixed model I am using: In a study, participants have been presented with 40 different news article headlines and indicated for each headline whether they would share the ...
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Actor-Partner-Interdependence-Model for longitudinal data (L-APIM) analysis for data with different number of intervention and no fixed interval

A friend recommended Stackexchange since I haven't found a suitable answer. I am currently trying to prepare my analysis of an Actor-Partner-Interdependence-Model for longitudinal data (L-APIM) with ...
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Cross-level longitudinal data analysis - which approach is best?

I have data from ~80 different companies, with anywhere from 1-10 employees from each company taking a survey once a month for 6 months. The measures are the same each month. However, the employees ...
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When should I care about the hierarchical structure of a few included studies for a meta-analysis (multiple independent groups, same outcome)?

I plan to meta-analyze proportion data (i.e. compliance rates in %) from >150 studies. Most of the studies will be single-group designs, but there will also be a few eligible multiple group studies ...
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Mediation Analysis with Categorical IV in R

I'm trying to conduct a 1-1-1 mediation analysis with HLM. My IV/treatment is a categorical variable indicating the type of the neighborhood (PW, PB, Mixed, PNB). 4 Levels. My mediator is a continuous ...
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Linear Mixed Model with repeated measure design, continuous and discrete predictors, and continuous predictor partially nested under discrete factor

Let's say I have the following data frame where subject ID (random factor) is completely crossed with the two other factors: IV1 and IV2. Additionally, IV2 is partially nested (or partially crossed) ...
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Correct notation for cross-level interaction

I am wondering if I am using the correct notation for a multilevel model with a cross-level interaction (i.e., a multilevel model with an interaction between level 1 and 2 covariates). Let $Y_{tj}$ be ...
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FIML (full information maximum likelihood) in R for Missing Data in Multilevel Model

Has anyone been able to find any package/function to run FIML in R for multilevel models? I know the lavaan package has a function for it, but it doesn't support mlm. I've only been able to find it in ...
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Forecasting a hierarchical time series (HTS) with a vector auto-regression (VAR) model - are they compatible?

I have a use case where I am testing the use of a VAR model with the FPP3 package in R. I have previously used an ARIMA model to forecast 2 variables separately, but because the variables are related ...
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Mixtures vs Multi-level models?

I'm confused on how mixture models and multi-level models are different (if at all.) Are there general rules for when to use one and not the other, pros/cons, etc?
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Need help with analyzing data from within subjects design study

I am planning to conduct a within-subjects design study, and I am wondering if data analysis can be done using multi-level analysis. IV and DV will be continuous variables. Moderator will be binary, ...
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Assessing which variable is more predictive in multilevel modeling. Question about seemingly conflicting results

I am analyzing data for a psychological study using multilevel models. I have a dependent variable (DV) and two predictors (A & B). DV, A, and B are all linear. I want to assess whether A or B is ...
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Leveraging hierarchical data in a GBM

A challenge that I encounter in a lot of modelling, is how to best handle hierarchical data for making prediction. A simple example of this is a basic (binary) classification problem, where I am ...
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How to compute the total standard deviation of the (true) effect sizes, σ, in random/mixed-effects meta-analytic models?

I have the following meta-analytic model (effect sizes nested within samples): ...
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having trouble with mixed-effects model

I conducted an experiment with a mixed design. Each participant was assigned to one of three experimental conditions and answered questions for all five experimental stimuli, and also answered some ...
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accounting for multi-scale spatial dependency in samples analysis

I have a spatially nested dataset as follows: 5 samples per cluster 5 clusters per plot 4 plots per site (2 habitats per site, 2 plots each) 7 sites overall I have: 5 samples * 5 clusters * 4 plots * ...
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is meta-analysis of combined raw/fully disaggregated data appropriate?

I have conducted several experiments that examine Reaction Time as the DV. Because I conducted them, I have the raw data for each. It makes sense to me that combining all the data (at the single-trial ...
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Multilevel Model Crossed Random Effects

I am analyzing a dataset using a multilevel model approach and have been recommended to look at using crossed random effects due to the structure of data. I've currently been treating my data as 2 ...
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Multilevel model when there is no variation in DV among some groups

I came across a study that claimed they used a logistic model with group-level clustered standard errors instead of a fixed-effect MLM because many groups did not have variation in the DV and so ...
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linear mixed effects model comparing recorded data to 'random' control data

I'm new to mixed-effects models and have some questions about the best way to analyze my data. Experimental Design: I have x-y coordinates for groups of 5 fish swimming around freely in a tank. We are ...
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Linear mixed model: Is subject-specific random effect for interaction meaningful if one factor is varied between-subjects?

I plan to apply a within-subjects design. However, currently, I am investigating my pilot data in which a between-subjects design was applied. The planned model comprises a subject-specific random ...

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