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, ...

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56 views
+50

Torn between PET-PEESE and multilevel approaches to meta-analysis: is there a happy medium?

I am currently working on a meta-analysis, for which I need to analyze multiple effect sizes nested within samples. I am partial to Cheung's (2014) three-level meta-analysis approach to meta-analyzing ...
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0answers
15 views

Comparison of observations in subgroups?

I have two groups, group A and group B. Each group is composed of subgroups, say A1, ..., An and B1, ..., Bm. Within each subgroup we have a different number of observations, say A1 would contain ...
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0answers
22 views

Multi-Level (Sparse) A/B Testing

I've been reading some articles about Bayesian A/B testing such as: http://engineering.richrelevance.com/bayesian-ab-tests/ but my application requires a framework for handling sparsity and group ...
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0answers
39 views

Different variance estimator for multilevel ordinal logistic regression in Stata and R

I estimate a multilevel ordinal logistic regression models in Stata and R, and receive different estimators for the variance and the covariance of the latent variable of the higher level. Among other ...
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10 views

Multilevel model with multiple level 2 variables

I am estimating a model where I want to know how the performance will vary across the students as influenced by their individual characteristics and aspects of their schools. Performance is the ...
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0answers
17 views

Multilevel models benefits vs. separate group models

What are the benefits of multilevel models vs. running a separate model for each group? My understanding is that MLM offer a method to effectively model interactions against all the base predictors. ...
2
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1answer
32 views

When is mu_a used in this STAN example?

I'm looking at an example of a random effects model with 2 random effects fit by Peter Li demonstrating how get models fit in lmer into STAN. The code for this and the accompanying data are stored ...
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0answers
11 views

STAN slowed by rank deficiency?

Does having a set of predictors which are not linearly separable slow down the model fit in STAN? If so, why? I have tried to test this, and it appears to slow down the fit. I fit a model with 10,000 ...
0
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1answer
20 views

Difference between multilevel GLM and mixed linear models when the family is Gaussian and link function is Identity?

In Stata 13, there is now the new command "meglm" (multilevel generalized linear models) to analyse hierarchical models. My question is, what is the difference between the "meglm" with family of ...
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0answers
11 views

How would you set up this multilevel model?

I have data at multiple levels and am trying to figure out how best to structure and analyze the data. Participants completed five measurement occasions in each of four conditions (that is, it was a ...
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0answers
26 views

What does (1|g1/g2) mean in a lmer formula?

What does this formula mean? lmer(y ~ (1|g1/g2)) equivalently: lmer(y ~ (1|g1) + (1|g1:g2) According to the PDF that I ...
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1answer
25 views

How is Group Level Term Estimated in Multilevel Model?

I understand from reading Gelman and Hill that for a multilevel model such as this one $$ y_i \sim N(\alpha_j + \beta X, \sigma^2) $$ $$ \alpha_j \sim N(\mu, \tau^2) $$ The $\alpha_j$ group-level ...
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19 views

three level random coefficients in jags

How do I specify a three-level model in Rjags with random intercepts and slopes. I can’t find help anywhere, not even in Gelman and Hill, so hence this question: In the model below, which is the ...
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0answers
16 views

Can you exclude one country as robustness check in multilevel cross-country model?

I am conducting a multilevel study in which individuals are nested in countries. As a common robustness check in normal linear regressions, we can exclude one or a few countries with special ...
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1answer
31 views

Multi-Level Modelling: Do I have 2 levels or 3 levels?

I have a question regarding multi-level modelling and whether this would be a 3 level. I am conducting a tms study testing the effects of tms on face naming and tool naming. Basically, each ...
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0answers
14 views

Model selection (BIC / AIC) ordinal multilevel model containing a factor score and/or part of the factor

I am building a ordinal multilevel model (Stata 13.1; meologit-command). At this stage I am trying to conduct my model selection using the BIC / AIC. I estimated several models and now I need some ...
2
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0answers
31 views

Compound Poisson Distributions: When, Why, and How To Split the Problem

I've just stumbled upon the Compound Poisson Distribution (CPD) and it seems to be precisely what I need. For the purposes of this post, let's suppose I have a store that sells many items of ...
2
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0answers
17 views

The Multilevel Linear Model with 3 Levels According to Guo and Zhao (2000)

I'm reading the following paper to learn about multilevel modeling: Multilevel Modeling for Binary Data Guang Guo and Hongxin Zhao Annual Review of Sociology Vol. 26, (2000), pp. 441-462 They ...
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0answers
15 views

imbalance in sample size at multilevel longitudinal data

I have longitudinal data (BMI level) measured at 3 time points and subjects are students nested to schools. The sample size in school level differs considerably (n=85 % in school 1, n=10 % in school ...
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0answers
8 views

Comparing trajectories of two outcome variables in longitudinal data

this is the situation: Study-type: prospective population-based (N = 4,000) with baseline (T1) and three follow-ups (T2 - T4) Between variable: cardiovascular health at T1 (good vs. poor) Within ...
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0answers
12 views

How does missing data (not at random) affect Bayesian models?

When I was a student learning about Bayesian models, we were taught that missing data was not a problem because they would be imputed. However I am wondering about how missing not at random (MNAR) ...
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0answers
26 views

Multilevel model with repeated data and time fixed effects?

I am using pooled cross sectional survey data to estimate prefernce for redistribution. I have 33 countries for 6 survey rounds covering the periods 2000-2013. I would like to estimate the effects ...
0
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0answers
23 views

ICC for growth model

I have searched quite a bit for this answer. Is there an ICC for unconditional growth models. Not the unconditional means model, but a growth model. I suppose I mean to ask is there a way to describe ...
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0answers
17 views

Analysis of insane factorial designs

I'm seriously thinking of doing the following experiment in the field of attention research. In this particular area there are some factors of importance that appear to modify participants' response ...
0
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1answer
12 views

Should I center time variant predictors in repeated measures multilevel models?

I have a multilevel model built coinsidering repeated measures on students. Students performance may vary depending on study hours and tutoring hours before each exam. Should I center the predictors ...
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1answer
78 views

What inputs, ideas or insight the community can offer on the subject “A simulation study of sample size for multilevel logistic regression.” [closed]

I have been assigned a topic on "A simulation study of sample size for multilevel logistic regression." I have searched the topic but found little reference on it. Could you please offer some ...
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0answers
18 views

Multilevel data - varying numbers of observations at lowest level

I have a number of entities and within each entity is a number of individuals. Each entity is of a different size. More specifically, each entity can have anywhere between 1 & ~1000 individuals. ...
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0answers
28 views

Syntax for a logistic multilevel analysis in R?

I am looking for advice on what package and syntax to use in R for modelling a logistic multilevel analysis with variables as follows: Dependent variable (binary) = 0 or 1 Independent variable 1 ...
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0answers
20 views

Fitting a multilevel AR1 in R

I have some short grouped time series data. I would like to fit a dynamic multilevel regression model in R, with random coefficients for the mean and first order auto-correlation in each group, and ...
0
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0answers
19 views

high standard error in random intercept model

I am fitting multilevel logistic regression to left without being seen (LWBS) by providers as dependent variable for each visit to 6 hospitals (random intercept of each hospitals). The total number ...
0
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1answer
41 views

Comparison between a multilevel and an unpooled model

Suppose we have fitted two models: a multilevel model and an unpooled model: m1=lmer(y~x+(1|group)) m2=lm(y~x+factor(group)-1) How can I understand which ...
0
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0answers
7 views

Redundant parameters in multilevel models

I am a bit confused about the use of redundant parameters in multilevel models in order to speed the convergence of the Gibbs sampler. I don't understand how the model should be reparametrized. ...
0
votes
0answers
14 views

Why do orthogonal complements come into play in the Granger representation?

Consider the Granger representation of a VAR model. (See : here). Can anyone explain me how in this representation Equation 1, page 4 the orthogonal complements of $\alpha$ and $\beta$ come into ...
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0answers
21 views

Multilevel version of one-sample t-test

I have a question about a multilevel model in which I model correct predictions made for a coin toss. Correct prediction are given 1 and incorrect 0. Since the coin toss is random, correct predictions ...
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0answers
16 views

Variance reduction in repeated measures multilevel model

I'm building a multilevel model where I have repeated measures of students' performance and some predictors (sex, age, studyhours, etc..). Sex does not vary with time, hours of study do vary. My ...
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2answers
75 views

Can I do a t-test to compare t-statistics?

I was trying to fit a 2-level "hierarchical model" all in one go, in MATLAB. But then realised it might be better to do the lower level first, then the higher level. Simply, I have 80 subjects, from ...
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0answers
28 views

Significant cross-level interaction despite lack of variance in level-1 slopes

I have a logistic HLM model with one level-1 predictor and without level-2 predictors. Random variance components are significant for intercepts, but far from significant (p>.5) for slopes. In my ...
2
votes
1answer
44 views

Why are the beta values provided in lmer() different than simple group means of observations?

In a 2-level mixed-effect model, the equation for level-1 is $$Y_{ij} = \beta_{0j} + r_{ij}$$ where $\beta_{0j}$ is the mean outcome for the $j$-th group. I ran the following model: ...
0
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0answers
32 views

Question about notation of expectation operators over multiple random processes

My question is what are suitable or accepted notations for taking expectations over multiple random processes in the same equation. Let a model for variable $y$ be given by $$y_{i ...
1
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0answers
71 views

Comparison of crossed random effects (mixed models): lmer vs. MCMCglmm

I read that lmer can handle independent (often labeled as crossed) random effects in mixed models. It seems to be possible with MCMCglmm as long as groups for the random effects are uniquely labeled. ...
1
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1answer
156 views

Interpretation of variance in multilevel logistic regression

Please help me to interpret the findings of my model. The specifications of the model are: Dependent variable: treatment (1) or no-treatment (0). Independent variables: age, number of drugs used, ...
1
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0answers
15 views

Individual factor significance in multilevel sPLS-DA

I recently was asked by reviewers to "include p-values" with my multilevel sparse partial least squares analysis. In brief, I have a nested design with two factors, say treatment and sampling region. ...
0
votes
1answer
30 views

Mixed model (Multilevel) with two INDEPENDENT Random Effects [lmer]

I like to estimate a mixed model with two Random Effects, that are independent of each other and among themselves. I use Panel data with a nested structure (counties $j$ nested within regions $i$). ...
0
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0answers
19 views

How to implement cross-classified(multiple group membership) repeated measure analysis?

Happy new year! I have a longitudinal dataset with 4 time points (2 measured in fall and spring semester of prek year, and 2 in fall and spring semester of k year). As a result, a same student has 2 ...
2
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0answers
17 views

Multilevel regression: question about notation

I have some difficulties in understanding the notation of multilevel regression models. Let's consider, for example, a varying intercept and varying slope model with just one level-I predictor. We ...
0
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1answer
67 views

Is this logit model a multilevel model, and what is the correct way to model it?

I am analyzing a sample of about 6000 actions carried out by about 500 multinational companies in about 80 countries during a 6 year period. Actions are carried out randomly, and are not longitudinal ...
3
votes
2answers
75 views

Which multilevel software should I choose?

I have used packages in R thus far for MLM, but now I need to do MLM with complex survey data, and as I understand it, none of the MLM packages in R can cope with the complex weighting needed to ...
6
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3answers
144 views

Are time series methods only good for forecasting?

Many time series methods are oriented solely in terms of forecasting (e.g., ARIMA). However, it seems like a growth curve modeling framework (i.e., random coefficient modeling) can do virtually ...
0
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1answer
51 views

Multi level regression with interaction using R lme4

I'd like to do a regression analysis with interactions, my data has two levels (school classes and pupils). My variables are: Predictor = dummy variable on Level 1, dependent Variable = metric on ...
1
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1answer
27 views

Multi-level, creating second level variable

I have some trouble coding my data for multi-level analysis. I'm doing research on test results of children. These children are grouped within classes, within schools. I'm using class as the highest ...