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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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A nonparametric residual bootstrap for random-effects models

This question regards ideas from "A novel bootstrap procedure for assessing the relationship between class size and achievement". The authors first describe a parametric bootstrap for random-effects ...
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Problems with singularity and a cross-level interaction

I have the following data structure: 200 Participants each saw 32 visual stimuli. These stimuli were manipulated on two properties (level-1 predictors). The participants came from two different ...
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1answer
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Multilevel analysis - interpretation not significant at level 1

I'm doing a multilevel analysis for the first time for my master thesis. The goal of my study was to create behaviour change through an intervention. Participants are measured for behaviour at 3 ...
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Is there a bias (atomistic fallacy) when I dis-aggregate higher-order variables to the individual level when using k-means clustering? [on hold]

I want to perform a k-means clustering, but I have a nested structure. However, I didn't find any packages supporting multilevel k-means clustering in R (or Python). Therefore, I'm thinking about dis-...
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Interpreting Random Effects for 3-level Multilevel Model

I made a land value analysis using a random-intercept multilevel model with 3 levels (lands nested in districts further nested in cities). The intercept is allowed to vary between each district and ...
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1answer
31 views

Mixed-effects models for within-subject psych experiment (in Stata)

I have a question about how to best analyze data from an experimental psychology study. Briefly, 250 participants were asked to assign four different pictures (Pictures A - D) to two different ...
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Model for taking a weighted average of a number of things, based on factors determining their significance

I am trying to model the following situation: There are a number of "events", each with a (real-valued) outcome. Ahead of each event, a varying number of parties can submit an estimate for the ...
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1answer
28 views

A non-linear regression model for within subject observations

I am trying to perform the equivalent of a repeated-measures ANOVA using data that have a non-linear relationship. There are two independent variables: Spacing between stimulus (10, 20, 35, 45, 60), ...
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Adding interaction term to multivariate parallel growth model nlme/lme4

I've been using examples from Grimm, Ram, and Estabrook (2017) to construct a parallel multivariate model to explore the relationship across time between two continuous variables, FS and Left_dlPFC. ...
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1answer
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In hierarchical model, how to choose groups that meet exchangeability, automatically?

In hierarchical model, we assume exchangeability. For example, y[i] ~ Norm(b0 + b1[groups[i]], sigma) and b1 ~ Norm(mu_b1, sd_b1) above, all groups are assumed exchangeable. But, it might be better ...
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Using marginal likelihood for weighting in bayesian hierarchical model?

I have data from a series of experiments. I have a simple model for generating the data these experiments which allows me to estimate a parameter. Some experiments do not conform to my model and ...
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How to conceptualise Hierarchial m-state time-event model with multiple absortion states;non exclusive states

I am designing a clinical study to investigate factors modifying the relationship between toxin exposure and its consequences. Since the original work is sensitive, I share an identical scenario. ...
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What is the difference between random-effects models, multilevel models and hierarchical models?

In the Bayesian paradigm, I have found examples of models that could be called any of the following: random-effects models multilevel models hierarchical models. Each of these categories even has ...
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Correlation between sentiment opinions of articles and sentiment of tweets. Comment on appropriate method [closed]

I want to measure a set of hashtags on twitter, and see if peoples sentiment on a set of hashtags is affected by the sentiment of newspaper articles that they retweet. What would be the best way to ...
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Multilevel model with nested groups

I am making a multi-level linear model in R using lmer Structure of my data is a bit convoluted There are 8 Bogs with 6 squares where damage is evaluated and 3 sweeps for insects. Squares 1,2 ...
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1answer
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Hierachical Random Mixed effect sizes

When using a mixed effect model the rule of thumb seems to be that you need at least 5 levels to use a random factor . Is this still True when you have a hieachical model. i.e A - 4 level factor B - ...
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What to use as a “stop” signal in a hierarchical LSTM model with continuous variable-length outputs

I am implementing a hierarchical sequence-to-sequence deep neural network model using long short-term memory (LSTM), where the bottom level of the hierarchy generates discrete outputs (characters from ...
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1answer
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groups, levels and denominator dof in mixed effect models

I am trying very hard (I am not a statistician) to understand the concepts of "groups" and "levels" in mixed effect models. In particular, I am trying to understand this in the context of the ...
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Multilevel modeling in R and Stata

I am trying to transfer from Stata to R. I have tried to fit a simple model in R and Stata with an identical large dataset (obs>60,000). The model has three levels: obs->individual->community. There ...
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why would do (F)GLS and multilevel modeling simultaneously?

To my knowledge, we could develop a multilevel model if we have a data that has a clustered structure in order to adjust for the auto correlation happening within each cluster. Then, we also learn ...
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1answer
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How to model a sequence of binary choices: Generalized Estimating Equations (gee)?

For the sake of example, let’s say this is a "costumer research study" with a 3 by 3 factorial design, in which I am studying whether customers make purchases or not depending on various factors. I ...
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How to compute intraclass correlation (ICC) for THREE-level logit hierarchical model?

I know that for a two level model the formula is: ICC = 𝜎^2/(𝜎^2+(π^2/3) But how can I calculate it for a three level logit MLM?
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glmer: Model failed to converge

My model is a three level MLM with dichotomous outcome using lme4::glmer (projects nested in Categories and then nested in Years): ...
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Linear Mixed Model Failing to Converge

I am attempting to run a Multilevel Mediation in R with overtime data (4 time points, 50 participants). I was hoping to create two new columns for each outcome and predictor variable, a baseline ...
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Comparing coefficients at different levels of multilevel model

I have a 2 level model with a related measure for both level (specifically I have people at level 1 and groups of people at level 2). ...
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ANCOVA: resolving hetrogeneity of regression slopes with multilevel modelling vs adding an interaction term

On the Wikipedia page for Multilevel model it is written that [M]ultilevel models can be used as an alternative to ANCOVA, where scores on the dependent variable are adjusted for covariates (e.g....
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Using random intercepts in a multilevel model as dependent variables in a linear model

I have a mixed model with 3 levels: individual, city, and state, and so I get random intercepts for both cities and states. I understand that since cities are nested in their state, their intercepts ...
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Mediation models using multilevel, longitudinal data

This is my first time working with longitudinal data and could use some advice about how to use the "time" variable in mediation analysis. I conducted a longitudinal study with fixed occasions (...
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Multilevel logistic regression for 3 by 3 factorial design? Sparse matrix problem

For the sake of example, let’s say this is a costumer research study. I have a binary outcome (x) that is either making a purchase or not making it. I have three independent variables: store ...
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Confused about multilevel analysis and non independence of observations

I'm still struggling with my understanding of multilevel analysis, wondering if it applies or not to my problem. I'v read here the following (where author gives an example of a multilevel model with ...
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1answer
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Is random slopes a specific kind of multilevel model?

I want to predict a binary outcome $Y$ with two predictors, one is continuous ($X$) and the other is categorical ($G$) and has $n$ levels. I believe relationship between $Y$ and $X$ varies among the $...
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1answer
25 views

Generation of synthetic data for Hierarchical clustering

I wanted to test various hierarchical clustering algorithms to check which algorithm performs best. For this, I was considering simulating some ground truth. Is the possible to generate a correlation ...
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Hierarchical Factor Analysis - Analyzing the factor structure of an identified factor

Problem Summary After performing an exploratory factor analysis one of the resulting factors "contains" a lot of variables which make its interpretation very hard. Since all the other factors have a ...
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Bayesian estimation in 2x2 mixed design study

I'm trying to correctly set up Bayesian parameter estimation for a mixed-design study with one 2-level between-groups independent variable and one 2-level within-subjects independent variable. The ...
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Need help selecting ROPE limits for a Bayesian multilevel model

I am using brms to estimate a Bayesian multilevel (mixed effects) zero-inflated beta regression model and want to use the HDI+ROPE (region of practical equivalence) ...
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1answer
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Coding nested factors for 3-level in rma.mv function of metafor package

I'm working collaboratively on an arm-based, network meta-analysis in the agricultural sciences. After carefully reviewing the Konstantopoulos walkthrough and Viechtbauer's slides to develop the code, ...
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1answer
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Analysis crossover clinical trial

I have data from a six-sequence 3-drug 3-phase crossover trial that had a 7-day baseline period pre-study (used to generate mean baseline value). My outcome is a non-parametric continuous variable ...
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Is it viable to run multilevel analysis on variables nested conceptually, and not necessarily by participants-groups?

I am trying to devise a model which predicts people's demand for more information. The model I'm contemplating has 2 levels of predictors that are not nested in terms of participants (for example, ...
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1answer
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Forecasting sales (in units) for thousand of products

I've got into this internship in a retail company and they asked me to think a way to forecast their daily sales (in units) in all their stores (with thousands of skus each one). At first I thought ...
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How to interpret interplots with marginal value of an cross-level-interaction

I need help regarding the interpretation of a plot created with the interplot function in R. The dependent Variable is the dummy Variable "Employment of mothers" (yes/no). The variable whose ...
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Different variables for different subgroups of linear model

Let's say I have a multiple linear model for a population of the form $y = \beta_0 + \beta_1x_1 + \beta_2x_2 + e$ There is a third variable I want to introduce that I believe significantly explains ...
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What model should I use? Time series count data grouped into provinces. R

I have daily observations on the count of a variable, with 1,000 daily observations across 15 different provinces, for a total of 15,000 observations. On certain days, there is an exposure, which may ...
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forced fixed intercept but lattice plot showed random intercept

I was running a model and something weird pops up. I ran a multi-level regression using the code below: ...
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Are Generalized Linear Models with random effects the frequentist version of a Bayesian Hierarchical Model?

In the Hierarchical Bayesian Model literature I often read of comparisons of the methods to GLM models, but with random effects. In the literature, is this the general consensus?
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In a Hierarchical Bayesian Model, how can we sample and see how a prior distribution looks like if it contains hyperparameters with hyperpriors?

I have a Bayesian Hierarchical Model that looks like: \begin{equation} Y_i \sim N(\mu, \sigma^2) \\ \mu \sim N(\mu_0, \sigma_0^2) \\ \sigma^2 \sim Gamma(1,1) \\ \mu_0 \sim N(0,1) \\ \sigma_0^2 \sim ...
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Interpretation Output lme (Intr)

I`m getting this output from R for my mixed model with lme package. The output seems to be making sense so far and I can interpret it. However I am wondering how I should interpret the correlation (...
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In a Multi-level Bayesian Hierarchical Model, would higher level parameters be affected by how they are jointly modeled in lower levels?

Suppose we have a Multi-level Hierarchical Model where: $$ \begin{equation} Y_{0i} \sim Bin(\theta_{0i}, n_{0i}) \\ Y_{1i} \sim Bin(\theta_{1i}, n_{1i}) \\ \theta_{0i} \sim Unif(0,1) \\ log\left(\...
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1answer
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When is the best to add control variables in multilevel modelling?

Is it better to add control variables before or after the main predictor variable while conducting a step-wise multilevel model?
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Chi2 or multilevel?

I am predicting smartphone app use. The research question is: do people use the smartphone app more when they get a reminder. If I have a dichotomous predictor (smartphone reminder) and a dichotomous ...