All Questions
349 questions
202
votes
1
answer
162k
views
Crossed vs nested random effects: how do they differ and how are they specified correctly in lme4?
Here is how I have understood nested vs. crossed random effects:
Nested random effects occur when a lower level factor appears only within a particular level of an upper level factor.
For ...
- 3,942
44
votes
1
answer
18k
views
How do you deal with "nested" variables in a regression model?
Consider a statistical problem where you have a response variable that you want to describe conditional on an explanatory ...
- 133k
42
votes
3
answers
68k
views
Difference between generalized linear models & generalized linear mixed models
I am wondering what the differences are between mixed and unmixed GLMs. For instance, in SPSS the drop down menu allows users to fit either:
...
- 689
52
votes
2
answers
131k
views
35
votes
2
answers
41k
views
Why do I get zero variance of a random effect in my mixed model, despite some variation in the data?
We’ve run a mixed effects logistic regression using the following syntax;
...
- 571
24
votes
1
answer
39k
views
Fitting a binomial GLMM (glmer) to a response variable that is a proportion or fraction
I'm hoping somebody can help with what I think is a relatively simple question, and I think I know the answer but without confirmation it has become something I just can't be certain of.
I have some ...
- 377
24
votes
2
answers
26k
views
How to apply binomial GLMM (glmer) to percentages rather than yes-no counts?
I have a repeated-measures experiment where the dependent variable is a percentage, and I have multiple factors as independent variables. I'd like to use glmer from ...
- 1,384
21
votes
1
answer
19k
views
How to fit a mixed model with response variable between 0 and 1?
I am trying to use lme4::glmer() to fit a binomial generalized mixed model (GLMM) with dependent variable that is not binary, but a continuous variable between zero ...
- 107k
37
votes
2
answers
36k
views
Diagnostics for generalized linear (mixed) models (specifically residuals)
I am currently struggling with finding the right model for difficult count data (dependent variable). I have tried various different models (mixed effects models are necessary for my kind of data) ...
- 1,185
42
votes
8
answers
26k
views
Under what conditions should one use multilevel/hierarchical analysis?
Under which conditions should someone consider using multilevel/hierarchical analysis as opposed to more basic/traditional analyses (e.g., ANOVA, OLS regression, etc.)? Are there any situations in ...
- 783
2
votes
1
answer
430
views
Both variables of my GLMM output are significant. Don't know how to interpret it?
This is more of an interpretation question than anything. I have run a GLMM with two fixed factors (both of which have two levels) and two random factors. The outputs from the model are as such:
<...
- 43
32
votes
3
answers
31k
views
What does "independent observations" mean?
I'm trying to understand what the assumption of independent observations means. Some definitions are:
"Two events are independent if and only if $P(a \cap b) = P(a) * P(b)$." (Statistical Terms ...
- 635
15
votes
1
answer
12k
views
OLS with clustered standard errors vs. multilevel modeling when the main interest is at the individual level [duplicate]
Possible Duplicate:
Under what conditions should one use multilevel/hierarchical analysis?
I have been reading various papers dealing with multilevel analysis, and to be honest, I am still ...
- 405
12
votes
1
answer
4k
views
Multilevel multivariate meta-regression
Background:
I'd like to conduct a meta-regression using studies which have (1) several outcomes/constructs (= multivariate) and (2) multiple effect sizes for every of these outcomes because of ...
- 205
46
votes
7
answers
24k
views
How to deal with hierarchical / nested data in machine learning
I'll explain my problem with an example. Suppose you want to predict the income of an individual given some attributes: {Age, Gender, Country, Region, City}. You have a training dataset like so
<...
- 1,904
19
votes
2
answers
15k
views
Random effect equal to 0 in generalized linear mixed model [duplicate]
Sorry if I'm missing something very obvious here but I am new to mixed effect modelling.
I am trying to model a binomial presence/absence response as a function of percentages of habitat within the ...
- 191
11
votes
2
answers
11k
views
Conditional vs. Marginal models
I have data with an outcome of 0 or 1 (binary) representing success or failure. I also have two comparison groups (Treatment vs. Control). Each subject in the study contributed 2 observations (the ...
- 815
6
votes
1
answer
4k
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 ...
- 955
4
votes
1
answer
6k
views
Forecasting hierarchical time series R package
I have to forecast a large set of (hierarchical) time series and since the R package hts allows for confidence intervals for their ensemble, I'd like to use it. I haven't found an example of how to ...
- 238
12
votes
4
answers
2k
views
Why is it OK to model demographics as random effects in bayesian multilevel models?
In Bayesian multilevel models (with, say, people nested within congressional districts) I sometimes see individual level demographic variables like race modeled as random effects.
So here’s a slightly ...
- 6,020
47
votes
2
answers
77k
views
How can I test whether a random effect is significant?
I am trying to understand when to use a random effect and when it is unnecessary. Ive been told a rule of thumb is if you have 4 or more groups/individuals which I do (15 individual moose). Some of ...
- 1,219
22
votes
4
answers
12k
views
How to calculate the confidence interval of the mean of means?
Imagine that you repeat an experiment three times. In each experiment, you collect triplicate measurements. The triplicates tend to be fairly close together, compared to the differences among the ...
- 21.2k
17
votes
1
answer
8k
views
Compute partial $\eta^2$ for all fixed effects anovas from a lme4 model
Disclamer: I wasn't sure where to post this question: CV or SO, but eventually decided to try here first
I've been asked by one of the reviewers to add effects sizes (preferably $\eta^2_p$ which is ...
- 557
31
votes
2
answers
98k
views
r glmer warnings: model fails to converge & model is nearly unidentifiable
I have seen questions about this on this forum, and I have also asked it myself in a previous post but I still haven't been able to solve my problem. Therefore I am trying again, formulating the ...
- 411
22
votes
5
answers
25k
views
How to assess the fit of a binomial GLMM fitted with lme4 (> 1.0)?
I have a GLMM with a binomial distribution and a logit link function and I have the feeling that an important aspect of the data is not well represented in the model.
To test this, I would like to ...
- 14.4k
21
votes
1
answer
21k
views
Difference between multilevel modelling and mixed effects models?
What is the difference between Multilevel/Hierarchical Modelling and Mixed Effects Models?
Wikipedia considers them to be the same, i.e. two different names for the same thing. But I think they are ...
- 1,094
19
votes
2
answers
10k
views
How will random effects with only 1 observation affect a generalized linear mixed model?
I have a data set in which the variable I'd like to use as a random effect only has a single observation for some levels. Based on the answers to previous questions, I've gathered that, in principle, ...
- 334
16
votes
1
answer
18k
views
Marginal model versus random-effects model – how to choose between them? An advice for a layman
In searching for any info about marginal model and random-effects model, and how to choose between them, I have found some info but it was more-or-less mathematical abstract explanation (like for ...
10
votes
1
answer
3k
views
Can I fit a mixed model with subjects that only have 1 observation?
I have a very large dataset where I have repeated measurements over time for individual locations. Some locations might have 10 data points and some locations have only 1 data point. I fit a mixed ...
- 265
9
votes
1
answer
4k
views
Resolving heteroscedasticity in Poisson GLMM
I have long-term collection data, and I'd like to test, whether the number of animals collected is influenced by weather effects. My model looks like below:
...
- 162
8
votes
1
answer
1k
views
Why do random effects require a minimum # of levels?
I have always heard random effects require a minimum number of levels to be correctly specified in a hierarchical (mixed-effects) model. I can admit to following this rule without question (mostly ...
- 2,071
4
votes
3
answers
11k
views
What are the assumptions of a Gamma GLM or GLMM for hypothesis testing?
What are the assumptions when doing hypothesis testing using a Gamma GLM or GLMM? Are the residuals suppose to be normally distributed and is heteroscedasticity a concern like the Gaussian (normal) ...
- 412
4
votes
1
answer
3k
views
Should quantitative predictors be transformed to be normally distributed?
I am always struggling with normality testing for quantitative predictors (no factors) and transforming them to normality.
If I am running a GLMM and my predictors are really non-normal, should I ...
- 1,635
41
votes
3
answers
10k
views
What's the relation between hierarchical models, neural networks, graphical models, bayesian networks?
They all seem to represent random variables by the nodes and (in)dependence via the (possibly directed) edges. I'm esp interested in a bayesian's point-of-view.
- 812
19
votes
1
answer
3k
views
How are PQL, REML, ML, Laplace, Gauss-Hermite related to each other?
While learning about the Generalized Linear Mixed Models, I often see the above terms. Sometimes it seems to me these are separate methods of estimation of (fixed? random? both?) effects, but when I ...
- 347
16
votes
1
answer
23k
views
Product Demand Forecasting for Thousands of Products Across Multiple Stores
I'm currently working on a demand forecasting task, with data on tens of thousands of products across a couple thousand stores. More specifically,I have a few years' worth of daily sales data per ...
- 739
14
votes
3
answers
5k
views
Multilevel model vs. separate models for each level
What are the advantages and disadvantages of running separate models vs. multilevel modeling?
More particularly, suppose a study examined patients nested within doctors' practices nested within ...
- 128k
14
votes
1
answer
16k
views
Calculating ICC for random-effects logistic regression
I'm running a logistic regression model in the form:
lmer(response~1+(1|site), family=binomial, REML = FALSE)
Normally I would calculate the ICC from the ...
- 175
11
votes
1
answer
12k
views
Model selection: can I compare the AIC from models of count data between linear and poisson models?
I am modeling count data (with offset / exposure parameter). My modeling strategy is use of a Poisson model and a negative binomial regression model. I compare model AICs, which are about -760 for my ...
- 6,724
2
votes
1
answer
2k
views
Computation and interpretation of marginal effects in a GLMM
I am currently working on a GLMM model which uses a Poisson distribution and need to compute and interpret marginal effects from this model.
The model outcome consists of a count (COUNT) collected ...
- 20.9k
1
vote
1
answer
667
views
Multilevel Modeling: Clustering by both individual and time, is this okay?
I'm trying to run a multilevel model where I have approximately 30 individuals and anywhere from 20-50 time points per individual. I can cluster them by the individual since the dataset is ...
- 221
1
vote
1
answer
5k
views
Accounting for time in repeated measures glmm, R
I have some count data of advanced stage juvenile snails in tanks that are sampled every 4 days for 4 sample points. I want to see how much the snail development stages change with a changing dosage ...
- 207
42
votes
4
answers
80k
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 ...
- 553
25
votes
2
answers
15k
views
Why is a $p(\sigma^2)\sim\text{IG(0.001, 0.001)}$ prior on variance considered weak?
Background
One of the most commonly used weak prior on variance is the inverse-gamma with parameters $\alpha =0.001, \beta=0.001$ (Gelman 2006).
However, this distribution has a 90%CI of ...
- 7,270
12
votes
2
answers
4k
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 ...
- 550
12
votes
1
answer
6k
views
Multiple Membership vs Crossed Random Effects
I see that there is a multiple-membership tag, but I can't find a good explanation of what a multiple membership model is, or how to go about fitting one.
In my limited understanding, it seem very ...
- 3,942
11
votes
2
answers
11k
views
Effect size in GLMM
In the output of a GLMM, using a binary variable as response variable and continuous variables as explanatory variables [family = binomial(link="logit")], I obtain, for each variable, an estimate ...
- 637
11
votes
1
answer
7k
views
Is it a must to include a random slope in a mixed model?
I am learning about fitting mixed models and I find when it is justified to include or exclude a random slope rather confusing.
Some tutorials suggest that although the maximal random structure should ...
- 125
10
votes
3
answers
407
views
Bacteria picked up on fingers after multiple surface contacts: non-normal data, repeated measures, crossed participants
Intro
I have participants who are repeatedly touching contaminated surfaces with E. coli in two conditions (A=wearing gloves, B=no gloves). I want to know if there's a difference between the amount ...
- 789
9
votes
1
answer
1k
views
Citation for ML vs. REML
Quick question: can anyone give me a citation that I can use to justify using ML when doing model comparisons?
Background: I am fitting some multilevel models in R using lme4, and I do a series of ...
- 989