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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10 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
13 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 ...
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0answers
16 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
16 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 ...
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1answer
10 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
77 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
15 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
25 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
17 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 ...
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0answers
18 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 ...
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1answer
36 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 ...
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0answers
4 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. ...
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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
17 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
13 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
70 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
22 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
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1answer
42 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: ...
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0answers
29 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 ...
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0answers
52 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. ...
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1answer
114 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, ...
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0answers
9 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. ...
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1answer
24 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 $i$). ...
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0answers
17 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 ...
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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 ...
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1answer
62 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 ...
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2answers
73 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 ...
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3answers
136 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 ...
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1answer
46 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 ...
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1answer
26 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 ...
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0answers
9 views

Searching class-intersections of many hierarchies for maximum/minimum values

Suppose we have some data for a large number of people (e.g. salary). Suppose further, that each person is classified in several hierarchical groups. E.g. they are classified by their location ...
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0answers
35 views

nested multilevel model for differential expression analysis

I have read several other postings regarding nested models, but they did not seem to exactly capture my particular case, and I'm a bit unsure how to proceed with analysis of my model. Any help would ...
5
votes
1answer
83 views

How many levels in multilevel modeling is too many?

This is pretty general, but what are the pros and cons of including additional levels in multilevel model (linear mixed model)? I have a data containing information on multilevel administrative ...
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0answers
12 views

Multiple groups - how to regularise estimate of level 1 parameters based on level 2

I am fitting some relatively complex structural equation models, but the specific model is not so important. I am estimating multigroup models, such that one parameter is completely free across ...
5
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2answers
88 views

On the utility of the intercept-slope correlation in multilevel models

In their book "Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling" (1999), Snijders & Bosker (ch. 8, section 8.2, page 119) said that the intercept-slope correlation, ...
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1answer
44 views

$R^2$ for mixed models = ICC?

I will be referring here to Nakagawa and Schielzeth (2013). As those authors state, $R^2$ for OLS regression could be defined as follows: $$R^2 = \frac{\sum^n_{i=1}(\bar{y} - ...
0
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1answer
78 views

Acceptable values for variance, aic and bic in multilevel models

I'm building a multilevel model from a sample of 820 observations at level 1 and 11 groups (level 2). I'm using stata xtmixed. Running the empty model (including ...
3
votes
1answer
220 views

Acceptable values for the intraclass correlation coefficient (empty model)

I'm using xtmixed in Stata to test a Hierarchical Linear Model. My problem is that variance at level 2 is about 4% of the total variance. So most of the variance is ...
0
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0answers
24 views

Need help with Random Effect specification in Multilevel (mixed models): nested Random Effects and a_priori known regimes (MCMCglmm)

I need some advices with the specification of the Random Effects in my Mixed model. I got Panel data from 500 (i) district nested in 50 (j) towns over 10 (t) years. There are 3 ex-ante known regimes ...
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0answers
12 views

Data At Varying Granularity

I'm sorry for asking such a simple question, but for some reason it is throwing me off. By "granularity" I mean level of the data. For example, say in the classic example of spam classification you ...
1
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1answer
31 views

Size multilevel logit model

I want to estimate a multilevel logit model. But I'm confused about the minimum number of groups and observations per group. What would be the minimum number of observations per group? My case: I ...
2
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0answers
35 views

Multilevel model for causal inference using observational data

I am trying to follow the lecture notes by Imbens/Wooldridge (http://www.nber.org/WNE/lect_10_diffindiffs.pdf) on difference-in-differences estimation. In page 4, they discuss the general framework ...
0
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0answers
26 views

Multilevel analysis, individual level and group level

I am investigating whether the air pollutant exposure during pregnancy has an impact on the infants' birth weight. The data I have include: 1)birth weight; 2)monthly air pollutant concentration ...
0
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0answers
12 views

multilevel spatio-temporal

I multilevel model includes county, city and year that the number of cancer (cancer of the response variable of the model I use a Poisson response) at these levels have been calculated And I want to ...
0
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0answers
33 views

Explaining why the slope varies in varying slope model?

When I fit a multilevel varying slope model, it is easy to summarize the variation in slope. However, I have not yet seen any materials that discusses how to explain such variation (i.e. what about ...
0
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0answers
20 views

Multilevel model when treatment occurs at intersection of non-nested groups?

I'm formulating a multilevel model in which my binary treatment happens in certain country-years. In other words, the treatment is at the intersection of certain countries (group 1) and certain years ...
0
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0answers
7 views

validation analysis

I am using multilevel logistic regression (random intercept) in SAS (PROC GLIMMIX)in my research. My question is how should I do validation analysis? What do I need to report in my paper as validation ...
0
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1answer
40 views

Time-variant & Time invariant & Time-related

In Longitudinal study, What are "Time-variant covariates", "Time invariant covariates" and "Time-related covariates"? and what is differences between them?
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0answers
29 views

How to analyse binary outcome data with between- and within subjects factors?

I am looking for the right statistical procedure to analyse my data (mixed design) with binary outcomes. Between-subjects variable: treatment (yes or no); experimentally manipulated Within-subjects ...
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0answers
45 views

Principal components analysis on nested data

I'm working on a piece of analysis that requires identifying a small set of variables that summarize the variation found in a larger set of principal observations on teacher practice. Given the nature ...