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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11 views

Significance of variance components in Stata output

This might be trivial, but I'm used to HLM7 software output and now I'm switching to Stata (xtmixed). To give an example imagine I have students (level1) nested ...
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0answers
9 views

Adding 2nd level variable into Multi-level Modelling in Stata

I'm used to HLM 7 software and now I'd like to switch to Stata, for multilevel modelling (xtmixed). To give an example imagine I have students(level1) nested within schools (level2). In HLM I can ...
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1answer
24 views

Multilevel modeling of response time data

I'm trying to figure out how to set up and analyze the following experiment. It's a basic reaction time-type experiment with 4 independent variables (2 levels each) and 1 dependent variable (RT). ...
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0answers
14 views

Sample size calculation for multilevel, longitudinal experiment

I'd be grateful for any advice about how to do a sample size calculation for the following design. We are interested in the impact of two variations of an intervention on hospital in-patients' ...
2
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1answer
71 views

Difference between random effect and random intercept model

I am looking at clustered data and because I was trained in economics I tend to look at fixed effects and random effects as solutions. An alternative would clearly be multi-level modelling. However, ...
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0answers
32 views

Help in fitting multilevel model using the MCMCglmm library in R

I am trying to fit a multivariate model using the R library MCMglmm. The data I have are testscores from c.a. 4736 students from different schools. For each student, also the socio-economic status ...
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1answer
18 views

Interpretation of correlations in multilevel anallysis [duplicate]

In the following multilevel analysis in R (taken from here, page 57): ...
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2answers
57 views

Appropriate way to treat [0,1]-distributed variables in HLM

Brief intro: I'm not really sure how to appropriately treat the dependent variables in a set of hierarchical linear models that I'm trying to run. In my models, Level 1 units are children and Level 2 ...
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1answer
33 views

Multilevel model where an interaction is a varying slope

I have a multilevel problem where I want to have a random intercept and a random slope. However the random slope is the interaction of two predictors. In this case, do I also have to allow random ...
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1answer
38 views

Interpreting the mathematical formula of a mixed effect model

I am a bit confused about the function of a parameter in setting up a linear mixed effect model (hierarchical/multilevel model). This is how I understand a (random intercept and slope) multilevel ...
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1answer
26 views

Why is collinearity a problem when imputing missing values?

I'm imputing missing values using R's mice package. My data has three numeric variables and a class variable so I am using a ...
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0answers
13 views

Cross level modeling in R, different levels of predictor, moderator and outcome variable

In the research that I am carrying out I have a moderation in which predictor, moderator and outcome variable are on the different levels: predictor and moderator on within level (the data were ...
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0answers
16 views

Question about Dummy Variable in Cross Level Interaction - GENLINEMIXED (SPSS)

Hi I am running linear GENLINEMIXED in SPSS 22. What does it mean when one of the dummy variables you are using in a model is significant when one group is coded as a reference group, and when you ...
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0answers
16 views

Three-way interaction in multilevel model

I am doing a multilevel Analysis in which I test whether the interaction between two Level 1-Predictors (IV1 and IV2) is moderated by a Level 2 predictor (IV3). The Level 2 predictor is a dichotomous ...
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1answer
36 views

Hausman's test for all $\beta$s – comparing FE vs RE models

I fit several two level models in SAS using PROC MIXED: an empty model with multilevel structure (null), a model with a level 2 covariate (partial model), and a ...
1
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1answer
72 views

Random factor nested in two fixed factors

I have read Random effect nested under fixed effect model in R, but I have a doubt: My data is on germling survivorship, I have Temperature as a fixed factor (2 ...
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0answers
18 views

Hierarchical Linear Modeling - Summation in Level 1

I'm currently trying to write a Level 1 model for the following research question. RQ: Does the school-level relationship between race and the proportion of reading proficient students (outcome) vary ...
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1answer
31 views

Multilevel Modeling and multiple testing

I am interested in working out the correct way to correct for multiple testing in multilevel models for longitudinal data, where I am investing a potential interaction between two predictors. My ...
2
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1answer
60 views

Multilevel modeling: longitudinal data with within-subjects factors

I have a data set with experimental data that I am analysing with multilevel modeling. Data are structured as follows: 24 Sessions 6 Subjects per Session 10 Rounds per Subject There was one ...
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0answers
19 views

ANOVA, unbalanced designs, missing data, and multiple comparisons

I am having several problems with my dataset and how best to analyze it. I have measured a series of plant phenology characteristics (with a seperate model for each one - I do not want to combine them ...
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0answers
10 views

Which model for survey analysis across countries and time

I'm analyzing data from a political opinion survey. The survey is administered once a year to roughly 1000 citizens from 18 different European countries. In a first step, I am interested in gauging ...
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0answers
41 views

How to run a multiple membership hierarchical model in Stata?

I have a dataset of educators and the courses that they designed. My original thought was to do a multilevel model where courses are nested within educators, and the outcome is whether the course ever ...
1
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0answers
72 views

simulate multi-level data for repeated measurements

I am trying to simulate multi-level data for repeated measurements. My design includes just one within subjects factor, no between-subject factor. Consider the case of three treatment conditions with ...
2
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1answer
20 views

Is there a limit to the number of time varying covariates in a discrete event history model

The case: I am investigating the impact of various predictors on the odds of migration using a discrete-time event history model within a multilevel framework. The outcome variable is dichotomous ...
2
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2answers
121 views

Multilevel models including random slopes: how to calculate variance

In a linear mixed model, you take the covariance between data into account by adding a random intercept per cluster. For example, you measure the effect of a drug campaign over time on students, and ...
2
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0answers
37 views

Formulating a hierarchical model in educational measurement

I'm having some trouble positing a model in levels for the question below. Question: How does the percentage of students born in the United States at the school level moderate the effect of the use ...
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0answers
40 views

question about multi-level modelling with nested data (R/Stata/SPSS)

I have a dataset composed of observations taken from 16 separate experimental panels, each nested into one of 4 conditions (Treatment A Level 1, Treatment A Level 2, Treatment B Level 1, Treatment B ...
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2answers
126 views

Is multilevel modelling simpler, more practical, or more convenient using Bayesian methods or frequentist methods?

In this community wiki page a twice-upvoted comment asserted by @probabilityislogic asserted that "Multi-level modelling is definitely easier for bayesian, especially conceptually." Is that true, and ...
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0answers
38 views

Should I bootstrap at the cluster level or the individual level?

I have a survival model with patients nested in hospitals that includes a random-effect for the hospitals. The random effect is gamma-distributed, and I am trying to report the 'relevance' of this ...
4
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1answer
55 views

Why is it necessary to use ML estimation instead of REML to compare multilevel linear models?

In Discovering Statistics Using SPSS 4e, Andy Field writes on p835 that: SPSS gives you the choice of two methods for estimating the parameters in the analysis: maximum likelihood (ML), which we ...
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1answer
42 views

Building a ML ordered logit regression model

I am building a ML ordered logistic regression. First of all, I really don't know if this is the best way to fit a model to my data, as I am not too confident in ML ordered logit regressions, compared ...
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0answers
21 views

Multiple Level Regression FDI

I am trying to work out an econometric model that has multiple layers, and I am not sure if it is feasible. I have 8 home countries that are investing in 3 host countries, and I am looking at the ...
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0answers
39 views

Model validation for multilevel logistic regrssion?

I have designed a multilevel logistic model using PROC GLIMMIX in SAS 9.3 for hierachical data based on pupil attainment where level-two is the school the pupil attends. I'm quite sure that my model ...
0
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0answers
11 views

what test for analysing level of agreement of users perception on species population trends from ordinal categorical data

This is my first post ever so I beg you please forgive me any mistake (I'm also super newbie in stats). I have this dataset that comes from interviews filled by users (divers) about their perception ...
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0answers
17 views

comparing simple(OLS) and multilevel regressions

Please, help me to understand how to compare two models - simple OLS and multilevel regression? Below you can see their pictures. In the simple regression there are 7 predictors including binary ...
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0answers
102 views

Repeated measures mixed model using lmer in R

I’m hoping to get some guidance in specifying a mixed model using the lme4 package in R. The study is quite straightforward. It’s a repeated measures design with pre/post measurements on the ...
0
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1answer
27 views

Some Basic things we need to do when we are doing text classification

I am working on a project where I have to do multi-label text classification. I want to understand that whether my approach is correct or I am missing something. I am using R to do it. Clean ...
2
votes
1answer
47 views

How to subset alternatives in nested multinomial logistic regression?

I am trying to predict whether or not captains in a particular groundfish fishery choose to fish on any given day and what variables may influence that decision. Originally I had planned on using ...
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0answers
33 views

Statistics for conditions with different number of levels

I have measured the brain activity in a group of 10 subjects who had to perform a task in real and imagined conditions, the task ...
4
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3answers
170 views

Repeated measures with single measurements

I have the following situation: General practitionar (gp), patient (pat) and consultation (cons). Each gp has several patient and each patient can have 1 and more consultations with a specific ...
3
votes
1answer
48 views

Sign of coefficient changes when contextual variables are added

I have an interpretation question. I am running binary multilevel models on whether or not households have bank accounts. Apart from relevant economic, social and demographical household level ...
6
votes
1answer
166 views

Random forest on multi-level/hierarchical-structured data

I am quite new to machine learning, CART-techniques and the like, and I hope my naivete isn't too obvious. How does Random Forest handle multi-level/hierarchical data structures (for example when ...
1
vote
1answer
30 views

How to expand sample subset with similar data

I would like to categorize a large sample and make some estimates for each category aka subset. The problem is that some subsets contain very few data points. How do I deal with that? For example: ...
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0answers
44 views

Random effects assumption and testing level 2 predictor variables

I was wondering if someone has any advice about the analysis I’m carrying out, or just give a recommended reference? I’m using a random effects modelling approach to account for clustering of patients ...
2
votes
0answers
43 views

Multilevel data with correlation within subjects

I have a dataset with 1206 deputies from two different chambers (1998 and 2002, respectively). In addition, there are 18 parties, and some deputies are in both chambers (the ones who were reelected). ...
2
votes
0answers
69 views

Multilevel model specification for count data (with overdispersion) in R

I would like to specify a multilevel model including the following variables: DV: count data, i.e. a score value between 0 and 13 (resulting from an additive index) for each individual Individual ...
2
votes
0answers
47 views

lmer giving worse performance than lm

I am having trouble training a model for nested data about house prices. Lets say my data looks like following: ...
6
votes
1answer
87 views

Notation for multilevel modeling

The formula one needs to specify for training a multilevel model (using lmer from lme4 R ...
1
vote
1answer
79 views

Dummy variables for linear models with multiple levels

I'm currently working with data which has continuous variables and a hierarchical structure attached to it, think of measuring blood pressure, size and weight of different domestic animals (cats, ...
0
votes
0answers
35 views

Interpretation of Random Slope in Multilevel models

i got a question regarding random slopes in hierarchical models (multilevel). I fit two models: Model 1: without random slope for covariate x (only random intercept) Model 2: random slope for ...