All Questions
1,501 questions with no upvoted or accepted answers
9
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0
answers
1k
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Should I cluster my standard errors even when using a multilevel model?
I've been reading up on multilevel modeling, and have noticed that many sources seem to frame it as an "alternative" to using cluster-robust standard errors.
My question: Are they really alternatives?...
- 91
9
votes
0
answers
2k
views
When and why do I have to use "trait" for multinomial multilevel models with MCMCglmm in R?
I want to estimate a multilevel multinomial logit model but I am struggling with the terminology and notation used by the R-package MCMCglmm. There is documentation ...
9
votes
1
answer
831
views
Comparing coefficients in multilevel models
Is it meaningful to compare the coefficients of two different predictors in multilevel model when the two are at different levels?
Specifically I have two variables which measure the same construct ...
- 1,039
8
votes
0
answers
226
views
Regression with dependent data with low dependence
Suppose you have data that is grouped in one way or another and therefore the assumption of independence is suspect. But you look at the intraclass correlation (or autocorrelation) and it is very ...
- 128k
8
votes
0
answers
923
views
Cross-validation in multi-level model
Suppose I want to estimate the out-of-sample prediction error of a boosted regression model that has random intercepts and slops. There are $G$ groups and $N$ observations. If I want to estimate the ...
- 3,925
8
votes
1
answer
802
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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7
votes
0
answers
1k
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Identification of peer/neighborhood effects in a multilevel framework
My question concerns estimation of “peer effects“ or “neighborhood effects” in a multilevel framework. The idea of such an effect is that the behavior of a household (on level-1) is influenced by the ...
- 175
6
votes
0
answers
1k
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What can I do whith this random effect conditional variance in lme4?
In the R package lme4, upon estimating a mixed-effects model I can retrieve the random effects and a corresponding variance using as.data.frame(ranef(model)). ...
- 71
6
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0
answers
433
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Simple trend analysis with unbalanced & short panel data
I have the following (unbalanced) panel data: yearly sustainability ratings (ESG) of ca. 2000 individual firms over a 11-year period. The average observations per firm only covers 5.3 periods. These ...
- 61
6
votes
0
answers
2k
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Hierarchical time-series forecasting with complex aggregation constraints
I'm trying to forecast multiple time-series with a hierarchical structure using the hts package by prof. Hyndman. However, the aggregation constraints are not sums ...
- 412
5
votes
0
answers
125
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Nested mixed effects model- am I missing an additional random effect?
Let's suppose that data is collected for clinics across the state. The clinics are located in different counties, but also some of the clinics are owned by large healthcare systems that are located in ...
- 133
5
votes
0
answers
250
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Calculating ICC for a beta-binomial GLMM
I understand that ICC in binomial GLMMs with a logit link can be calculated via R, where the residual deviance is (pi ^ 2) / 3. However, this is assuming that the ...
- 51
5
votes
0
answers
309
views
How can I find and categorise the effect size of a single coefficient in a multiple regression?
Question
How do I find the effect size for the different hierarchical multiple-level regressions used by papers in my review? And how do I categorise their effect size?
Detail
I’m publishing a ...
- 51
5
votes
0
answers
909
views
Prediction intervals for HTS forecasting
So I have a lot of time series with a hierarchical structure, and need to produce forecast for each base series and its aggregates by the hierarchical structure.
I have decided to produce forecast ...
- 61
5
votes
0
answers
2k
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ROC curves for repeated measures
I am trying to model ROC curves for a longitudinal dataset where participants were measured between 1-13 times. Time is not of interest but the fact that the measurements are autocorrelated an issue. ...
5
votes
0
answers
4k
views
No value or "."returned for Mauchly's Test of Sphericity in SPSS
I am learning how to do a Two-Way Repeated Measures ANOVA in SPSS but when I try to check the Mauchly's Test of Sphericity Significance value it only displays a single decimal point. It is also ...
- 495
5
votes
1
answer
327
views
Model relation between two rank variables where ranks are nested within subjects in one variable
I have elicited 10 attributes from $N$ subjects. Each subject rank ordered his own 10 attributes from the most to the least important one. I am interested in the relation between the order of ...
- 291
5
votes
0
answers
187
views
How to mitigate the hierarchical error propagation in tree-structured classification
Suppose we have a multi-class classification problem, where the number of classes $K \geq 3$
We use a tree structure of multiple SVMs to divide and conquer the problem, with one example in the figure ...
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5
votes
0
answers
2k
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Interpreting the variance of random effects in Mixed Linear Models?
When fitting the following simple model, using the 'lme4' R package and including a fixed and random slope term, I get:
...
- 429
5
votes
0
answers
2k
views
Hierarchical (multilevel, random-effects) Gaussian process regression
If we have a $J$ groups of predictor, outcome (univariate) variable pairs,
$$
\{(y_{j1}, x_{j1}) \ldots (y_{jn_j}, x_{jn_j})\}, \quad\text{for $j \in 1\cdots J$},
$$
a hiearchical linear regression ...
- 283
5
votes
0
answers
813
views
How does GEE (Generalized Estimating Equation) treat different cluster size?
I have a population of 200,000+ patients and their hospital visit information. I'm trying to see if having a certain disease would have an effect on whether they will have readmission or not (this is ...
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5
votes
0
answers
2k
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Q: Exploratory factor analysis in R
I am trying to do an exploratory factor analysis (EFA) in R with oblique (promax) rotation.
From Wikipedia,
In oblique rotation, one gets both a pattern matrix and a structure
matrix. The ...
- 862
5
votes
0
answers
509
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 ...
- 51
5
votes
0
answers
1k
views
Hierarchical regression with dummy variables
I need to perform hierarchical regression with dummy variables. I also need to check moderation by introducing in the model interactions of these dummy variables and the moderator. My questions are:
...
- 101
5
votes
0
answers
853
views
How to implement a two-stage hierarchical model of time series data in R?
I'm currently working with a data set that consists of a monthly case count for several sites, along with a number of site-specific covariates. We're trying to estimate the effect of one of them on ...
- 23.7k
5
votes
0
answers
236
views
Dynamic consistency and multilevel models using lmer
I've been using nlme and more recently lmer to fit multi-level models of time course data using orthogonal polynomials. My ...
- 940
5
votes
0
answers
270
views
Analysis hierarchical circular mixture data
I have circular data such that multiple human participants were, each shown a color from a color wheel, asked to remember it for a "retention interval", then report it back by clicking a ...
- 14k
4
votes
1
answer
45
views
How to Simulate a Multilevel Predictor Variable with Both L1 and L2 Variance Components?
I'm working on simulating multilevel data where I have a predictor variable measured at Level 1 (L1), which has both L1 and L2 variance components. For example, I want to simulate a socio-economic ...
- 153
4
votes
0
answers
67
views
Adjustment in a regression for community level aggregation of individual level data
In a cross-sectional study based on geographical multilevel regression, the authors used both individual-level data AND features generated by aggregating the same individual data in the community and ...
- 2,939
4
votes
1
answer
113
views
Methods for drawing population inferences from multiple sub-population datasets
What would be an appropriate model or method for making inferences about a broader population quantity from multiple quantities representing subsets of the population?
Imagine, as an example, that I ...
- 1,312
4
votes
0
answers
927
views
Python Implemenatation of SPSS's Two-Step Clustering
I want to perform a clustering on data with ~40 binary features. I was recommended the two-step approach by Chiu et al.. They basically use a BIRCH variant to determine pre-clusters and then perform ...
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4
votes
1
answer
251
views
Seeking textbook reference for 2 way chi square tests for main effects and interaction
I seek a textbook example of the application of chi square tests for main effects and interaction for categorical data, as in a 2x6 table. I plan to use this to help me be sure I can correctly use ...
- 3,427
4
votes
0
answers
138
views
Mixed Effects Model: Writing and Interpreting Models with Two and Three-Way Interaction Terms and No Random Intercept
Question: Have I correctly translated my lmer models into formulas depicting each individual level, as well as the composite formula? Specific questions about my work below.
Information about my ...
- 363
4
votes
0
answers
219
views
What’s the right multilevel model to address this meta-analysis?
I have a sample of about 4,000 $r$ (that is, Pearson correlation), $\chi^2$, $t-$, or $F-$ tests reported in psychology journals. These tests have been drawn randomly from a larger dataset with about ...
4
votes
0
answers
138
views
Can we identify whether random effects are nested or crossed from a lme4 fit?
My colleagues and I are working on a suite of lmer post-estimation tools for a R package we are developing. One of the tools is an ICC function that would calculate ...
- 5,890
4
votes
0
answers
381
views
AIC Comparison for MLM with Different Distributions
Thank you in advance for your time and consideration! I am a non-mathematically-inclined graduate student in communication just learning multilevel modeling.
We are running different models - some ...
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4
votes
0
answers
584
views
Confused about multilevel analysis and non independence of observations
I'm still struggling with my understanding of multilevel analysis, wondering if it applies or not to my problem. I'v read here the following (where author gives an example of a multilevel model with ...
- 393
4
votes
0
answers
123
views
Normal Covariance Estimation
I have a hierarchical model and I'm struggling to develop an estimator of the covariance of a normal distribution. This is my specific problem. There are $n$ latent $p$-dimensional vectors,
$$\...
- 1,327
4
votes
0
answers
71
views
Dependence between parameters in Bayesian multilevel regression
I am working on a Bayesian multilevel regression model, which is specified as
$$
y_{ij}=x_{ij}'\beta+\delta_j+\varepsilon_{ij}\\
\delta_j=\gamma_{\operatorname{region}(j)}+\eta_j
$$
where $i$ indexes ...
- 2,498
4
votes
1
answer
655
views
GLMM with time-series covariance and binary response variable?
I have a binary response variable that was measured at irregular time intervals for a number of individuals. I want to fit a GLMM that accounts for the time-series covariance within individuals.
I ...
- 1,096
4
votes
0
answers
507
views
Principal component regression (PCR) with some of the original predictors left out of PCA
I just recently started learning about principal component regression (PCR) and I'm wondering if it's possible to use both principal components and original variables as predictors of a given outcome (...
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4
votes
0
answers
1k
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Multivariate regression in Tensorflow where dependent variables also depend on each other
Dear Stackoverflow community,
I would like to understand how to implement a multivariate regression in Tensorflow, where all the dependent variables yn depend on both input variables xn as well as ...
- 141
4
votes
0
answers
670
views
Identical mixed models in SPSS and R nlme, with different degrees of freedom. Which to trust and why?
I am analyzing a multilevel dataset with an AR(1) error structure and random intercept and slope. I fit what I believe is the exact same model in SPSS and R- my coefficients and standard errors are ...
- 141
4
votes
0
answers
44
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 ...
4
votes
0
answers
272
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 ...
- 284
4
votes
0
answers
216
views
What is the difference between bi-level linear models and models with interaction terms?
My question is triggered by this question. I can't see that it has been asked here before, even though it looks like a natural enough question.
Suppose I have hierarchical data. The Wikipedia article ...
- 1,042
4
votes
0
answers
75
views
Fixed parameter estimates of parent factors in a nested design
Summary: What is happening with parameter estimates of factors that are the 'parents' of nested factors?
Data: My analysis involves testing the effect of different parameter settings for automatic ...
- 376
4
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0
answers
1k
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Assessing Cannibalization, intervention of new mobile app on monthly sales
I am a beginner in statistics and looking for suggestions from you all on the approach for one of my study.
For my study, there is a company which sells products via its online website (lets call it ...
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4
votes
0
answers
3k
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Binomial logistic regression in SPSS using survey weights
I am running a logistic regression in SPSS with a sample that uses survey weights. The sample size is 1000 and the weights are along the lines of .86 or 1.23 depending on the case. I am using the ...
4
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0
answers
915
views
How to do centering if I have a quadratic term?
I have been trying to run a multilevel model with both a linear and a quadratic term for income as my main variables of interest. It looks something like:
\begin{eqnarray}
&&y_{ij}=\beta_{0j}+\...
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