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, ...

learn more… | top users | synonyms (2)

0
votes
0answers
12 views

Should I use GEE, Multilevel or Cox regression?

I am interested in the relationship between the number of hours worked per week and the chances of getting an illness. My dataset consists of 47 subjects, the predictor variable hours worked per week ...
0
votes
1answer
20 views

How to test repeated, nested, count data

I have samples from an experiment in which I have counted cells. I took 2 pictures of each kidney, photographing both kidneys of each subject. Each individual belongs to a group (infection). My ...
3
votes
0answers
21 views

Approaches to fast estimation of new levels of a hierarchical linear model from new data

I have a hierarchical linear model I've applied to a dataset in which the effect of a factor on my outcome measure can vary for different people. Say I have a new individual for whom I have some ...
0
votes
1answer
35 views
0
votes
0answers
16 views

Understanding Multilevel graphs

Sorry for the simple question. Could someone help explain how I would describe the findings in multilevel model graph. I'm looking at between region variation in disease cases with temperature as ...
0
votes
0answers
19 views

Multilevel model using negative binomial

I'm trying to look at between region variation (5 regions in total) in disease cases and the influence of climatic factors. How do interpret the variance given such a small value i.e variance when ...
0
votes
0answers
6 views

SPSS Mixed model with imputed data and model LLC scores

I am supposed to build several models (it is multilevel analysis of students from different schools). I used multiple imputation for missing data after running MVA and pattern analysis. Now I have 5 ...
0
votes
0answers
6 views

Can I conduct multilevel analysis with two aggregated data sources?

I have two data sources with completely different specific individuals. One contains individuals answering whether or not they have watched the movie "Lego", and the other date source contains ...
0
votes
0answers
12 views

What's the difference between multilevel models(nesting) and multiple regression(adjusting)?

I am studying from "statistics with r by Andy". He gave an example of hierarchical model as: we measured anxiety among children in two classrooms (the teacher in class 1 is nervous and the other one ...
0
votes
0answers
19 views

Regression on Survey analysis across 50 states

I ran a survey across all 50 states in the US. The goal is to see if there is a correlation between people's love for the state and the population growth % over 5 years. The survey has 15 questions - ...
0
votes
0answers
19 views

Multiple t-tests on group averages vs multi-level model

I did an experiment with N participants, each tested with 10 stimuli with type 1 and 2 variants. 10 instances of each stimulus. I want to see if response to item type 1 was significantly different ...
1
vote
0answers
19 views

Should I centre or standardise variables in a linear mixed model analysis?

My study is looking at skin lesions in pigs. I have 2 partially cross-classified random factors (weaning pen and finishing pen) and several predictor variables. I have centred pig weights by pen ...
3
votes
0answers
36 views

Difference between hierarchical Bayes and random parameter/effects models?

From my limited understanding, the difference is mainly that hierarchical Bayes (HB) incorporates parameter distribution priors that will "constrain" the individual parameters to one side of the ...
0
votes
1answer
33 views

What is the difference between a mixture model and a hierarchical model?

What is the difference between mixture and hierarchical models? Are they of the same nature with different names or they are totally different things? If there are any references, I will be happy to ...
0
votes
0answers
9 views

Compare Sexes within Groups in Multilevel Data

I have a large data set including about 50 groups of 6 participants, with about 2/3 same-sex groups and 1/3 mixed-sex groups. Based on previous research, one hypothesis is that women cooperate more ...
0
votes
0answers
17 views

Performing a 2-1-1 multilevel mediation in r

I'm interested in the relationships between the following three variables: religiosity, teleological explanations of daily events, and gratitude resulting from those events. I have collected data ...
0
votes
1answer
24 views

How do we put various multivariable data in cluster bucket

A data with multivariable of mixed types (Nominal and Continuous) are clustered using R package of Daisy/Agenes. How are we going to put the variables in the cluster bucket I was thinking to put max ...
1
vote
0answers
38 views

Fixed effect not siginificant in multi-level model, what else to report besides significance?

I'm studying the effects of a teaching style intervention on student motivation. I use multi-level modeling since students are nested within teachers. The condition main effect is not significant (p = ...
1
vote
0answers
14 views

Regression with dependent variable at a higher level than independent variable

I have a dataset with unique observations for each independent variable and observations at a grouped level for each dependent variable. What is the best model to asses if these two variable are ...
1
vote
1answer
22 views

Hierarchical Weibull model: choice of parameterization

I am experimenting with fitting a Bayesian hierarchical model using right-censored and Weibull distributed time-to-first-event data. However, I have some issues that might be related to the ...
0
votes
0answers
5 views

1 continous predictor and dependent variable measured in 4 different conditions - multilevel analysis?

My experimental design involves one continuous independent variable (score in the questionnaire) and continous variable which is measured in 4 different conditions (different type of the stimuli). I ...
0
votes
1answer
25 views

Multilevel models

I would have a question on multilevel models, which is related to a particular case that I am considering. The question is related to the number of my groups and the number of measures in each of ...
1
vote
0answers
29 views

Summarizing multiple clustering results

I'm working on a problem where observations are being clustered within groups but I'd also like to compare the groups. However I am not sure of the best way to compare the groups. In total I have ...
0
votes
0answers
20 views

Multilevel and multivariate statistics

I'm considering classes for next semester and I have a choice between 2: Multivariate statistics and analysis Hierarchical linear modeling and growth models I'm wondering which of these courses ...
0
votes
0answers
21 views

Multilevel Poisson Model

Following some reading I have tried for the first time to use multilevel poisson model to look at risk factors for disease cases in sheep in 5 English regions. The overall aim is to find out if the ...
0
votes
0answers
21 views

Median odds ratio for 2-level binominal model in r

I'm a true beginner in calculating multilevel models in R. Now, I have a 2-level model with a binominal outcome variable. Does anyone know how to calculate the Median Odds Ratio for this model in R? ...
1
vote
0answers
25 views

Hierarchical Linear Modeling With Binary Outcomes

I am an ungrad helping out with a Prof and have had no luck trying to figure out what to do with the data. I have age, gender, experimental condition (Condition 1, 2, 3-between subjects), ...
0
votes
1answer
26 views

Multi level model in R: error comparing models due to different number of observations

I am running a linear multi level model in R. The predictor variable is called "OAI", and the response variable is called "Ens", I am allowing the intercepts and slopes to vary with "ID". Here is a ...
0
votes
0answers
17 views

Multilevel model with group level outcome

I have a group-level outcome (team-level performance ratings); and individual-level predictors (individual-level responses from team members), and would like to fit a latent-variable multilevel model ...
4
votes
0answers
28 views

When to use fixed effects vs using cluster SEs?

Suppose you have a single cross-section of data where individuals are located within groups (e.g. students within schools) and you wish to estimate a model of the form ...
2
votes
1answer
38 views

Multi-level Bayesian hierarchical regression using rjags

I am trying to to implement a Bayesian hierarchical Model in R. I have a few predictor variables (2 metric and one categorical) and am trying to predict quarterly home sales in the US. Each sales ...
2
votes
0answers
52 views

Matching with multilevel data

I've got a dataset where a treatment $W$ has been applied to units $i$ within clusters $c$. $W$ is constant within each cluster. As a component of an algoritm that I'm implementing (which was ...
1
vote
1answer
23 views

Multilevel models vs GLMMs for correlated clustered data

What is the difference between the Generalized Linear Mixed Model (GLMM) and a multilevel model?
1
vote
0answers
33 views

How to implement a two-level beta regression?

I am working with Time-series Cross-section data and my response variable is a proportion ranging from 0 to 1 (including 0 values but no 1s observed). Beta regressions, and especially the ...
2
votes
0answers
39 views

How to cluster/analyze effect sizes after meta-analysis? (meta-meta-analysis)

For a research project I compared persons with and without a specific disorder on basically every published outcome I could find. The idea was to get some sort of profile of this disorder (i.e. skills ...
2
votes
0answers
15 views

nnet vs glmer for multilevel logit

I have data where I'm interested in the effect of treatment on individual decisions: Options 1, 2, & 3. Individuals made multiple decisions (level 1) in groups (level 2). I want to know the ...
0
votes
0answers
13 views

Multiple imputation of lungitudal, time-unstructured data in SPSS

I have a longitudinal data set of home measurements of some disease-related physiological parameters that have been sampled throughout a period of 16 months. Of course there is some degree of missing ...
0
votes
0answers
12 views

Accounting for uncertainty in random slope estimation

My question relates to calculating the uncertainty associated with the estimation of slopes in a varying intercept, varying slope hierarchical model. I would like to calculate the effect of a ...
2
votes
0answers
21 views

Trying to analyze a blocked, multilevel design with unbalanced, repeated measures

The research question(s): Do road crossings over streams influence the abundance of stream-dwelling salamanders (SDS)? Do these road crossings influence SDS abundances differently downstream than ...
0
votes
0answers
25 views

Are there easy tools for visualizing the hierarchical structure of mixed models?

I'd like to produce graphs of the data structure of mixed models, like this from Schielzeth & Nakagawa 2013 I am teaching a seminar on mixed models to 1st year grad students and want to ...
0
votes
0answers
21 views

How to specify this linear mixed model in R

I have data from an experiment in which subjects (primary school students) viewed a set of stimuli, identical for all subjects, with each stimulus defined in terms of values on two continuous ...
0
votes
0answers
25 views

likelihood-ratio test - models were not all fitted to the same size of dataset

I would like to test different predictors in a series of multi-level models for a dichotomous dependent variable. I use the glmer funtion from R's lme4 package to estimate my models. First step was a ...
1
vote
1answer
84 views

Multilevel model with nested repeated measures design

I am new with R and I am trying to use multilevel modelling for my dataset using the function glmer (for a binomial outcome variable) and ...
0
votes
0answers
11 views

How can the fit of a multilevel model including a new fixed effect improve if the fixed effect is not significant at all

I am trying to fit a multilevel model using the lmer package in R. My model has two levels (the upper level is "country"). I include a level 2 fixed effect (i.e., constant for each country). Here is ...
1
vote
1answer
49 views

Unsupervised Learning on Multilevel/Multidimensional Data

I am working on a case-control study, where I for each individual have high dimensional data (like illustrated in the image). I would like to do both PCA analysis and Clustering on this data, but ...
1
vote
0answers
35 views

Dummy Variables vs Multilevel Model

I have some household surveys taken across three villages in West Africa. I want to look at relationships between different variables, and I want to account for village-level effects. The two ways I ...
0
votes
0answers
57 views

Which method to be used to analyze this data?

You are building a model to predict disease risk from patient measurements such as age, blood pressure, family history, etc. You suspect that some features will have a non-linear effect: for example ...
0
votes
0answers
24 views

Extremely large variance in multilevel model

I am running a three-level logistic regression model on Stata, and I'm getting extremely high residual variances (~10E+08) at level 2 and 3. I can't seem to be able to understand what is happening. ...
0
votes
0answers
50 views

Correcting specific non normal distribution

I have run a multilevel model (time series cross section data; xtmixed) and am checking if the assumptions hold. Given the non-normality of my residuals, and after having corrected potential linearity ...
0
votes
0answers
45 views

ICC in a multi level model with two random effects

My understanding is that intraclass correlation gives you an idea of how much variance your level two factor can explain in overall variance of the dependent variable. It is supposed to give an ...