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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clustering standard errors within MLMs/lme4

Is it possible to use both cluster standard errors and multilevel models together and how does one implement this in R? In my set up I am running a conjoint experiment in 26 countries with 2000 participants per country. Like any conjoint experiment…
4
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1 answer

Nested random effects and related fixed effects

I have cross-national panel data and I'd like to know the impact of IV on a binary student-level outcome DV I'd like to include a nested random effect that takes into account that which school the student is in will affect the outcome, and that…
3
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2 answers

Multilevel model for repeated measures data using lme4 in R

I have a data frame with post and follow-up measurements for approximately 200 people. In the study, we try to find out if there is a correlation between sports participation and distress symptoms. We have two measurement periods (post and…
Timon Doo
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Estimating and plotting predicted probabilities from a multilevel ordinal logit (clmm)

I'm estimating a multilevel ordinal logit with one interaction term using clmm. The coefficients I get are interesting and statistically significant and I now want to compute and plot predicted probabilities. In doing so, it may be relevant to…
3
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1 answer

Interpretation of variables in multi-level regression with random effects

I have a dataset that looks like the one below (first 5 rows shown). CPA is an observed result from an experiment (treatment) on different advertising flights. Flights are hierarchically grouped in campaigns. campaign_uid flight_uid treatment …
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1 answer

Interactions and Rlang: Error: ! `class` must be a character vector, not a list

So, I keep getting an error when trying to plot Johnson-neyman plots with the sim_slopes function of the Interactions package. library(interactions) m <- lm(mpg ~ hp * wt, data = mtcars) sim_slopes(m, pred = hp, modx = wt, jnplot =…
Ttytamaki
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Can I specify a random intercept in a conditional logit model?

In conditional logit models, global intercepts cannot be estimated as they do not influence the conditional probability of a positive outcome within groups. I understand the intercept term gets cancelled out in the derivation of the equation, just…
Olifa
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2
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1 answer

lme4 1.1-27.1 error: pwrssUpdate did not converge in (maxit) iterations

Sorry that this error has been discussed before, each answer on stackoverflow seems specific to the data I'm attempting to run the following negative binomial model in lme4: Model5.binomial<-glmer.nb(countvariable ~ waves + var1 + dummycodedvar2 +…
JustinB
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Graphing a multilevel model in Stata

I'm looking for suggestions on how to graph a multilevel model I'm working on. I'm working with some covariates which I nest around one group: country. Therefore my model looks like this: Code: melogit trust_d i.soldicontatti##c.individualism…
2
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1 answer

Multilevel Regression with 3 Levels

I want to make a multilevel regression with 3 levels. I have data from a survey, where I have the information in which county the participants are living. So, I can also dinstinguish between East and West Germany. In the picture you can see what I…
2
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1 answer

how to run a double cross-classified 3-level hierarchical linear model in R? DIF in HLM

I am trying out a novel hierarchical linear model but the data structure makes me wonder if this is even possible in R. My previous attempts at the model were incorrectly specified (oops) and now I'm not sure how to deal with this piece of work. My…
Aaron
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ggplot random intercept goes vertical instead of horizontal

I am trying to plot a random intercept model that also contains the line of best fit. The model is supposed to show the relationship between team culture and helpful behaviors. Thus, all individuals are nested in teams. When I try to plot my data, I…
J.Sabree
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R Lmer model fails to converge, nearly unidentifiable (very large eigenvalue)/ singular fit

I had the two following warnings when running a multilevel model: Warning messages: 1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model failed to converge with max|grad| = 103.424 (tol = 0.002, component 1) 2: In…
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finding the within-person SD from a null model lme output

I just wanted to make sure I'm interpreting my lme output correctly. I've set up a null model because I was told I could find the within-persons SD this way (Nelzek, 2012 MLM chapter). But the chapter is written in formulas, not in R code. Here's…
2
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0 answers

Extract conditional modes from multilevel logistic regression

I am estimating a multilevel logistic regression predicting the likelihood of making an error on a given trial. The model has random effects of participant, scenario, and actor, as well as fixed effects based on two variables and their interaction.…
David Johnson
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