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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GLMER for panel data - question and concerns about setting up variables

I have panel data (a dummy data representation is below), with two time periods where each person responded at TIME = 1, and TIME = 2. I am interested in how exposure affects a change in opinion from ...
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Random slope in multitrial experiment

I have a within subject multitrial experiment with 3 factors. Task type: 2 levels Difficulty condition: 3 levels Time bin: 7 levels (categorical variable, not continuous) So each task type containes ...
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Understanding Exchangability in Bayesian Hierarchical Models

I have a group of $k$ experiments (indexed by $j=1...k$) and each experiment $j$ produces a set of $n_j$ datapoints denoted as $y_{ij}$ such that $i\in\{1,...,n_j\}$. Meanwhile, $y_{ij}$ is ...
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Multi-Level Modelling in Metanalysis where effect size is in percentage

I was wondering if someone can help. I have a meta-analysis where I have 5 outcomes and 10 included studies. The studies are classic prevalence/ epidemiological studies, so not 2 groups. I want to ...
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Multilevel structural equation modeling with interaction between latent variables: designing the model and choosing the appropriate software

This has been a bit of a conundrum I've been trying to solve for a while and relates to a question I asked a while ago. I am trying to build a 4-level structural equation model (SEM) with latent ...
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Should I incorporate sex as a control variable or use multi-level modelling?

I'm doing a linear regression model to look at how socio-economic status impacts children's height. My dataset will be survey data for both males and females. To me, it makes sense to control for sex, ...
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Interpreting multilevel mediation analysis in R with continuous predictor

I conducted an experience sampling study (with measurement occasions, lvl-1, nested in participants, lvl-2) and now want to investigate, whether daily flow experience (lvl-1) mediates the relationship ...
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Is it possible to compare the relative importance of variables in a multilevel model?

I will be running a multilevel model and I have covariates at the subject- and group- levels. Is there a way to compare their relative importance? I found a paper < https://digitalcommons.wayne....
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why Maxmimum likelihood estimation is used for multilevel analysis?

In multi-level modeling, why not use OLS? are there any specific reasons behind that? And why do people recommend using restricted maximum likelihood rather than maximum likelihood in multi-model data?...
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Weekly demand prediction of different product types at various depots

I have a dataset containing daily demand values of different product types at different depots. The products do not have the same demand and there are many cases where there has been no demand for a ...
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Integrating out random effect from hierarchical model

Given $Y_{ij}$, $M_j$, and $R_i$ as observables, my probablistic model is $$ Y_{ij} = \theta_{i}M_j + \varepsilon_{ij}\\ \theta_{i} = \beta R_i + \phi_{i} \\ \varepsilon_{ij} \sim N(0, \sigma), \...
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ICC vs Repeated Measures ANOVA to Justify Multilevel Model

I have heard of using ICCs to determine if there is variability to justify using a multilevel (i.e., mixed effects, hierarchical) model. However, I've recently seen studies examine whether there is a ...
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How to interpret hierarchical regression output that has insignificant IV in step 2, but still shows significant F

I'm working through a 4-step hierarchical regression where the first step is to add grouping variables (student standing, gender, & previous experience) and the 2nd step as adding a psychological ...
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How to specify mixed effects model for repeated dyadic data

I am trying to figure out how to specify the model for a special case of repeated-measures dyadic data. To provide an illustration (which is analogous to my research project), let us say that I want ...
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Linear mixed model (repeated measurements) on HUGE dataset

I have a huge dataset with measurements of 21k genes across 11k samples. The measurements, called expression, represent (roughly) how "active" that gene is in the cells of the sample (in ...
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Statistical test to compare teachers of students taking tests

Suppose I have two teachers $T_1$ and $T_2$, who teach students $S_{11}, S_{12}, \dots S_{1n}$ and $S_{21}, S_{22}, \dots S_{2n}$ who then answer questions $Q_1, \dots Q_m$, giving us two $n \times m$ ...
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41 views

How to Collapse data with weighted averages for the variables? [closed]

I have a dataset containing postal codes, district numbers and some other variables such as income, age, education levels etc from about 10,000 observations. I need to Collapse(mean) variables 'income'...
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Fitting a 3-level multilevel model with very large dataset (N around 17 000 000)

I need to fit a model of the following type: fit <- lmer(outcome ~ 1 + (1 | sub_sub_group) + (1 | sub_group) + (1 | group), data = df) I am interested not only ...
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Estimating confidence intervals for ICCs in a multilevel Poisson model

Can anyone help me with this in R? I need the conf. intervals for the ICC in a glmmTMB model. I know I should either go for bootstrapping or something Raykov 2015 ...
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Simulating Hierarchical Data

I want to simulate a dataset that has a "grand mean", and then group means (with some deviation from the grand mean). Nevertheless, I have a bit of a problem conceptualising the problem: if ...
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Household recruitment based on variable reduction technique

I want to recruit Households based on spend on liquor by identifying set of features which increases the average spend. Altogether there are 70 features having mixed type e.g. Type of house, ...
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Linear Mixed-Effect Model: how to assign two subjects (random effects) of one observation to the same random effects term?

I have a performance measure (dependent variable "DV"), which I want to model using a hierarchical linear model (lmer()). The DV is a performance measure for which two subjects have ...
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Can Machine Learning Models Recover "Experimental, Design and Hierarchical Structures" Within the Data?

Can Machine Learning Models Recover "Experimental, Design and Hierarchical Structures" Within the Data? At times, real world data can contain "embedded structures" - these ...
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Interpreting effects in a meta analysis random intercepts regression model

I have a random intercepts model with two different clustering levels: studies and countries within which these studies were made. So, my interest is to estimate a model to figure out the grand mean ...
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Stat test that allows comparing means across groups

I have a dataset involving a dependent (numerical) variable and 2 indipendent (one nominal and the other numerical) variables. My nominal variable involves 4 groups, with each group being split into ...
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Exploratory factor analysis during ageing

I am performing some study, using subjects from different age cohorts. For each subject I measure the expression levels of some genes. Sometimes I have missing values. I try to find two sets of ...
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24 views

How to conduct subgroup analysis for multilevel meta-analysis model?

I would like to compare meta-analytic estimates from 2 subgroups using the metafor package. I came across this helpful guide, but I am using multi-level models (for multiple effect sizes within ...
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1answer
24 views

Longitudinal multilevel models: deleting the baseline timepoint

I'm reading a paper which reports a multilevel model with random intercepts and slopes in which individual people's score on a scale of anxiety is assessed at five different timepoints. So the ...
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Opportunity Evaluation within excel

I'm a student of data analytics. I've the following raw data https://1drv.ms/x/s!Amd7BXzYs7AVhAqQGtBZLHzQ1xZ6 The main goal as for finished example :https://1drv.ms/x/s!Amd7BXzYs7AVhAsWa0e5yvqPhuRf?e=...
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"Group mean centering" a dummy Variable in R for multilevel analysis: how can i do this?

have somebody an idea of how to group mean center a dummy Level 1 predictor in R? Enders & Tofighi (2007) describe a method to center a dummy variable through substracting the proportion of the ...
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How to assess model fit for multilevel SEM (using Mplus)?

According to a preprint chapter by Sadikaj et al. (2019), the standard way to establish model fit for multilevel SEM is (1) develop a measurement model at each level if latent variables are included ...
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Regression for hierarchical time series

I have a dataset with time series A, B and C from different countries. These time series have different starting points, missing values, and irregular intervals (only weekdays). Instead of forecasting,...
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Explained variance with nested data?

I have vector representations of text $\vec{y}$ for participant $i$ in condition $j$. The data is unbalanced, though: Some participants are in more conditions than others. I am interested in the share ...
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Repeated Measurment HLM

I have a mixed data set with 3 repeated measurements. At each measurement time point, the subject received one of three experimental manipulations (TMS). The order in which the experimental ...
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1answer
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Is standardize always necessary when predictors having very different scales?

I am running a two-level mixed model, where individual economic status and GDP per capita (PPP) are predictors, and subjective well-being (SWB) is outcome. Two predictors (economic status, PPP) are ...
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Can anyone help me figure out power for this multilevel model, given I don't yet have access to data?

I have a multilevel model - looking at treatment and gender effects of an intervention across 4 timepoints, with a sample size of 434, and I'm struggling to find code in R to calculate the power, ...
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Bayesian method for determining needed usage rate of second cancerous mole treatment to improve overall population cancer rate

Let's say I have a method that identifies and treats cancerous skin moles. Not everyone has such moles but, just to be safe and since it won't cause any harm, I've used the method on every single ...
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Why do cutpoints and effects in ordinal regression become inflated when nested observations are used?

I've been trying to conduct some power analyses for a hierarchical, ordinal regression. In a simple case a group is measured at Time 1, treated, and measured again afterwards at Time 2. I simulate ...
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Correct syntax for random coefficient in Cox with time-varying predictors using R coxme

thanks for helping! I am testing a repeated measures dataset (multiple rows per participant) in a multilevel Cox regression with time-varying predictors. I'm trying to see if effects vary by assessor. ...
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1answer
108 views

Multilevel model - Hessian matrix not positive definitive error, but only for certain covariance structures

I am analyzing data using multilevel modeling / growth curve analysis. For my best fit model, using likelihood ratio tests, I have landed on a random quadratic time interaction model (see syntax below)...
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37 views

Inconsistent posterior estimates in Beta-Binomial likelihood vs Binomial in Bayesian, multilevel models?

In this Google Colab, I've simulated Binomial count data and compared the performance of Binomial-likelihood and Beta-Binomial-likelihood models. Both models have the same Beta prior on theta, the ...
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Validity of significance testing random effects in SPSS a multilevel model / growth curve analysis

I am running a series of growth curve models in SPSS, with 3 separate psychological variables as outcomes. I would like to test for the statistical significance of random effects (both the variance ...
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28 views

Package/procedure for causal mediation analysis with two mediators in multilevel data

I have an epidemiological cohort with multiple survey waves. The independent variable and mediators of interest are numeric and normal enough while the dependent variable (self perceived general ...
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What type of variable can be level-2 variable? Does higher ICC indicate better multilevel model?

I am working on a dataset that has 27 countries, and I would like to investigate how does individual economic status influences well-being. Well-being was measured by WHO-Five well-being Index (WHO-5)....
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Scenario of implementing mixed-effects model

I'm currently analyzing data with repeated measurements. However, the interested studied variables with fixed effects were collected after the occurrence of the response variables. I think usually the ...
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Predicted treatment effect for causally related conditions

Let's say there are two medical conditions $A$ and $B$ that are causally-related, i.e. that they share a common etiological process $C$. For example, $A$ and $B$ could be related autoimmune conditions ...
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Combining Individual Studies with Multilevel Models

In one of the papers I read, the authors combine the data of two individual studies that are very similar to one another (Study 1 does not include a control group, but Study 2 does) to increase ...
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1answer
27 views

Analyzing a likert-type item data with repeated measures with logistic ordinal regression

I'm analyzing some Likert-type item for my thesis. After a quick research, I figured out, that instead of using a least-squares regression as conventionally, a logit or probit ordinal regression model ...
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Should I be using multilevel model with two or three levels?

I am predicting enrolment numbers for schools and I am unsure if I should use a three-level or two-level model. From my understanding, the data is nested, where each school is nested within a postcode....
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Data with Hierarchical Structure and Multicollinearity (E.g. ZIP Postal Codes)

I always had the following question: Can data having "naturally occurring hierarchical structure" be transformed to better make use of this hierarchical structure at different levels? To ...

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