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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3
votes
2answers
38 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 ...
4
votes
1answer
72 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
votes
1answer
26 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
vote
1answer
22 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 ...
0
votes
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 ...
1
vote
0answers
19 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 ...
4
votes
1answer
43 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 ...
1
vote
0answers
10 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 ...
3
votes
0answers
37 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, ...
1
vote
0answers
24 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
votes
1answer
26 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
84 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
votes
0answers
11 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 ...
1
vote
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
vote
1answer
23 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
votes
0answers
19 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
votes
0answers
19 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
votes
0answers
8 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
votes
0answers
27 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
votes
0answers
13 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
votes
0answers
6 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
votes
1answer
23 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?
0
votes
0answers
25 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 ...
1
vote
0answers
33 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 ...
0
votes
0answers
72 views

Multilevel analysis in R and Stata

I am trying to replicate a multilevel logistic analysis which uses a dyadic time series data set and R. As for my part, I am using the same data set but Stata. The original syntax has the following ...
0
votes
0answers
33 views

How to report mixed effects logistic regression

I have several models predicting different binary outcomes as a function of time (binary variable: before/after intervention) and age (ranges 4 to 14), measured in different students within different ...
1
vote
0answers
18 views

Comparing two curves with peaks

I have a question about analysis method and I would be very grateful for the help! So, I have two groups: Active and Placebo, each group is measured for 20 different concentrations (from 1 to 20) 6 ...
0
votes
0answers
11 views

initial status X time interaction

I am modeling change in a continuous variable over time using linear mixed modeling in SPSS. I would like to examine the possibility that initial status (i.e., pretest performance on the DV) interacts ...
0
votes
0answers
24 views

nonsignificant predictor becomes significant

This may be a question with an obvious answer. I am trying to predict change in a continuous variable over time using a linear mixed model in SPSS. There are 4 time points. Ultimately, I would like to ...
0
votes
0answers
15 views

multilevel mediation with a proportion dependent variable sem

I am attempting to test an indirect path in a multilevel dataset with an outcome that is a proportion. The data are a collection of variables related to various qualities of potential support ...
0
votes
0answers
30 views

Need help setting up multilevel logistic regression

I am trying to see the effect of a certain intervention in schools. The outcome variable is binary. We have students within schools. Also students' age is a covariate (doesn't changed before and after ...
1
vote
0answers
7 views

Quantifying Reliability of Qualitative Testing

If a visual grading system is implemented to calculate the correlation between exterior and interior conditions (i.g., good, medium, bad), and a sample is taken from a known population to test the ...
0
votes
0answers
30 views

Confidence intervals of proportions for clustered data

I am trying to compute the proportion of "yes"'s in data that is clustered (participants within cities). If I ignore the cities, I get very nice and narrow confidence intervals. If I compute the ...
0
votes
0answers
17 views

Estimating proportions in a non-nested multilevel Bayesian model

Data: x: 1/0 successes (~ 800 data points) c: city code (1 to 78) t: "time of measurement", 1 (morning), 2 (afternoon), 3 (evening), 4 (night) The problem: I would like to estimate the ...
0
votes
1answer
49 views

Undefined real result error at WinBUGS

I am currently working on my thesis and interested in estimating a multilevel differential item functioning model and I using at WinBUGS. Until I had done model check-up, there are no errors. However, ...
1
vote
0answers
41 views

Assumptions of Linear Mixed Model

I had data with repeated measurement and nested design. Conventional ANOVA requires strict control on homogeneity of variance and repeated measurement ANOVA requires assumption of sphericity. ...
1
vote
1answer
48 views

Multilevel: Can I include two dummy variables of a 7-dummy-set into a random slope?

I am calculating a two-level linear multilevel analysis. A look at the random intercept random slope model showed me a significant decrease in my model deviance if I include two dummy variables. Those ...
1
vote
0answers
15 views

How to share weights of between regression models when you learning them simultaneously?

I have many phenomenons which I want to model them as lasso regression problem. every phenomenon have it's own distinct features set. but for some phenomenons, the subset of features set are the ...
2
votes
3answers
71 views

Can I do a t-test to test significance? [closed]

I need a statistical test to determine if one group of ten classrooms with different numbers of students in each class has a class average on a test. Group two has 12 classrooms also with different ...
3
votes
1answer
101 views

Multilevel logistic regression with a random slope(s)

I would like to specify a two-level logistic regression model with random intercept and random slope. Dependent variable: hospitalization (1) or no-hospitalization (0). Independent variables: age, ...
1
vote
0answers
42 views

Fitting a partially clustered/nested design using lmer

I have a study where clustering occurs in one condition but not the other. In the treatment group I have repeated measurements on individuals who are nested within families. And in the control ...
1
vote
1answer
55 views

Cross-sectional Regression (individual level) with a few country-level variables

I have a small sample of 50 cross-sectional firms and 3 or 4 distinct explanatory variables -- all on the individual level. No time dimension. So far, I could employ OLS (I am using Stata: ...
4
votes
2answers
154 views

Is it ok to use a random intercept model without testing for random slopes?

In university we calculated a random intercept model for two-level nested data. We compared the random intercept model with all level-1 variable with the random intercept model with all level-1 and ...
1
vote
2answers
69 views

Survey weights at multiple levels

I am dealing with some data from a household travel survey, and I have a question about how to best use the survey weights that are provided. The structure is that households are sampled, and all ...
0
votes
0answers
32 views

How to interpret 3 main effects when an interaction exists for only two of the variables?

I've been searching for interpretation guidance regarding the below problem, but all the resources I've seen have been fully crossed (i.e., all variables included in the interaction term). Below is a ...
3
votes
0answers
204 views

What does “independent observations” mean?

I'm trying to understand what the assumption of independent observations means. Some definitions are 1 "the occurrence of one event doesn't change the probability for another". 2 "sampling of one ...
1
vote
0answers
21 views

Predicting dropout in an ordered process: Cox regression, autoregressive model, multilevel modeling?

I am working on a project in which I collected data about 100 people’s steps in an ordered process. All took at least one step, with some continuing up to a fourth step. Each person either drops out ...
0
votes
0answers
17 views

Feature/Variable selection to accompany mixed models?

I am trying to conduct an exploratory/data mining analysis to discover what socioeconomic factors best predict grade-school performance in children. I have a dataset with about 50000 ...
0
votes
0answers
14 views

In non-nested models, should group indicators have seperate mean for each?

I'm studying hierarchical model using Gelman & Hill book. On pg. 289, they discuss the following non-nested model. There's a psychological experiments of pilots, with $n= 40$ data point ...
2
votes
0answers
51 views

Mixed model with lmer: Variance of residuals should give the same as level 1 variance?

I expected that the variance of residuals from a mixed model computed by, for example, lmer should give the same as the residual variance from the summary output. ...