Questions tagged [multilevel-analysis]

Statistical methods appropriate for the analysis of data sets comprising several levels of hierarchy of units of analysis (e.g., students nested in classes nested in schools; observations nested in patients nested in hospitals). If you can refer to more specific models like mixed-model or glmm, please do so.

Overview

"Multilevel analysis is a general term referring to statistical methods appropriate for the analysis of data sets comprising several types of unit of analysis. The levels in the multilevel analysis are another name for the different types of unit of analysis. Each level of analysis will correspond to a population, so that multilevel studies will refer to several populations..."

-T.A.B. Snijders, Multilevel Analysis, p. 673-677 in M. Lewis-Beck, A.E. Bryman, and T.F. Liao (eds.), The SAGE Encyclopedia of Social Science Research Methods (Volume II). Sage, 2003.

Related tags

  • for linear multilevel models, or HLMs
  • for models with random intercepts
  • for models with random intercepts and slopes
  • for generalized linear mixed models (binary, ordinal, count response)
  • and for R implementations
  • for Stata implementation
  • for Bayesian models comprising several levels of hierarchy of priors and hyperpriors

Please use these tags to make your question more specific and easier to find.

164 questions
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Imputation missing data for MLM in R

Maybe anyone can help me with this question. I conducted a follow-up study and obviously now have to face missing data. Now I am considering how to impute the missing data at best using MLM in R (f.e. participants concluded the follow up 2 survey,…
Timon Doo
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Why does coxph() combined with cluster() give much smaller standard errors than other methods to adjust for clustering (e.g. coxme() or frailty()?

I am working on a dataset to test the association between empirical antibiotics (variable emp, the antibiotics are cefuroxime or ceftriaxone compared with a reference antibiotic) and 30-day mortality (variable mort30). The data comes from patients…
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Modelling multinomial dependent variable with longitudinal/panel data (R)

I'm having some trouble with an analyses I want to conduct and were wondering if there are any alternatives. Essentially I have a longitudinal dataset (or panel data), and a dependent variable (group membership) that is categorical and time…
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Survey design for multilevel analysis

I am new in using R, and I need to run a multilevel analysis (two-phase design on two levels) using Cox frailty survival model on a survey data (Nigeria Demographic and Health Survey Data). My problem is how to write the design weight using the two…
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Multilevel model using glmer: Singularity issue

I'm using R to run a logistic multilevel model with random intercepts. I'm using the frequentist approach (glmer). I'm not able to use Bayesian methods due to the research centre's policy. When I run my code it says that my model is singular. I'm…
bella1998
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compare different multi level regressions

i am struggeling at the following: My idea is to analyse the development (slope) of an output of different multi level regressions. The output is matched in my data with 2 different timepoints. I have 3 predictors (senseofhumor, seriousness,…
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Is it normal that glmer returns no variance of intercept?

I am trying to run a multi-level model to account for the fact that votes for a country's presidential elections may be nested within groups (depending of voters' mother tongues, places of residence etc.). In order to do so, I use the glmer function…
Mikokorico
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Fixed effect and random intercept models using "lavaan" in R: advice on coding

I´m trying to fit some path models (i.e. all variables are observed; no latent variables) using “lavaan” in R. I´ve been able to do this successfully for a model where the data are completely pooled (Model 1, below). But, the data are grouped and…
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How to perform parallel growth mixture modeling (GMM) using R?

Usually, i'm using "lcmm" package in R - in order to perform growth mixture modeling (GMM). However, i want to create a classification or groups based on two variables rather than one. I've read that this kind of modeling called "parallel growth…
Shay
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How to obtain monotonic effect of ordered factor predictor in lme4 package

I want to obtain a monotonic effect for an ordinal predictor with the function lmer() from the package lme4. My reference is the estimate that can be obtained with mo() in the brms package (a more developed review of monotonic effects for ordinal…
Crimc
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How do I sum on the outter most level of a multi index (row)?

I am trying to figure out how to sum on the outer most level of my multi-index. So I want to sum the COUNTS column based on the individual operators, and all the shops listed for…
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How to interpret significant test of moderators and null percentage of explained variance in meta-analysis using "metafor" package?

I'm currently working on a meta-analysis of proportions (number of mosquitoes transmitting a disease/number of mosquitoes tested), using metafor package (Viechtbauer, 2010). My aim is to compute a summarized effect size for each of 5 mosquitoes…
a.drouin
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Error running multi-level interclass correlation

I am trying to run mult.icc to calculate multiple ICC's from a dataset. Data has group ID column, and 9 variables. All variables are numeric. I have run the following: mult.icc(data[,c("v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9")], …
Anna
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Multi-level models + pymc3.glm

I need to fit a multi-level linear model using PyMC3 and I really like the glm api, because of the conciseness it provides. I would like to ask if and how this can be done. This blog post I found mentions that: glm() does not play nice with…
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How do I conduct a Multilevel Model/Regression in Python?

I have yearly data over time (longitudinal data) with repeated measures for many of the subjects. I think I need multilevel modeling/regressions to deal with sure-to-be correlated clusters of measurements for the same individuals over time. The data…
exlo
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