All Questions
2,982 questions
6
votes
2
answers
1k
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Justifying the Need for Mixed Effects Models (aka. LME, MLM, etc.)
Firstly, I am not an expert in using multi-level modelling (MLM), and I have read this and this questions, however, my question is slightly different in the sense that method 2 below is not mentioned.
...
- 441
6
votes
1
answer
458
views
Why GEE estimates are smaller than GLMM?
Both are estimators that maximize the marginal likelihood, only GLMM does so by first considering the conditional probability, while GEE assumes a covariance structure of the marginal probability ...
- 3,680
6
votes
1
answer
3k
views
Distinct results between "emmeans" and "multcomp" - package in multi level model
I have calculated a multi-level model with a biomarker as dependent variable (which was measured three time), a 5-level factor variable called „module“ as predictor (which is an intervention including ...
- 61
6
votes
2
answers
1k
views
Conditional intraclass correlation (ICC) from a linear mixed model as evidence for test-retest reliability?
In my experiment with two conditions (between-subjects design), participants completed a single-item scale three times: (1) before the experimental manipulation, (2) after the experimental ...
- 67
6
votes
1
answer
2k
views
What are the consequences of including unnecessary random effects?
In mixed models (GLMMs), random effects are often used to account for non-independence between observations e.g. of the same patient, or of animals from the same farm. I sometimes see multiple random ...
- 385
6
votes
1
answer
12k
views
Conditional logistic regression vs GLMM in R
I have paired data (GWAS case/control study) and I have heard using conditional logistic regression or generalized linear mixed models (GLMM) is appropriate. Which should I use in this case? Why would ...
- 10.2k
6
votes
1
answer
748
views
Using Bayesian model diagrams to present both model description and results (posteriors)?
The model diagrams in "Doing Bayesian Data Analysis", John Kruschke creates diagrams like this:
To represent The following BUGS/JAGS code:
He discusses this representation in his related blog post, ...
- 7,270
6
votes
2
answers
812
views
Possible identifiability issue in hierarchical model
I'm trying to fit some data using a hierarchical normal model
$y_i \sim N(\theta_i,\sigma^2)$
$\theta_i \sim N(\mu, \sigma_\theta^2)$
$(\mu,\sigma^2,\sigma_\theta^2) \sim diffuse$
I fit this ...
- 61
6
votes
2
answers
900
views
Deriving mathematical model of pLSA
After knowing how LSA works, I went on continue reading on pLSA but couldn't really make sense of the mathematical formula. This is what I get from wikipedia (other academic papers/tutorial show ...
- 207
6
votes
1
answer
222
views
Should I give more weight to goodness of fit or to conceptual approach?. Example
I am running mixed effects models with percentage data.
I run my model using a gaussian distribution approach. AIC=-258, my conditional and marginal pseudo-R squares were 0.33 and 0.11 respectively (...
- 421
6
votes
1
answer
12k
views
GLMER not converging
Here is a sample of 20 rows from some data I'm working with (everything below is consistent with the full dataset):
...
- 519
6
votes
2
answers
1k
views
Confused about meaning of subject-specific coefficients in a binomial generalised mixed-effects model
In *A Comparison of Cluster-Specific and Population-Averaged Approaches for Analyzing Correlated Binary Data*, Neuhas, Kalbfleisch, and Hauck state:
"With the cluster-specific approach, the ...
- 2,187
6
votes
1
answer
3k
views
Testing significance of a random effect glmmADMB model
Below is the output from a model of novel object test scores fit with the nbinom1 (quasi-Poisson) option in glmmADMB. I used ...
- 61
6
votes
1
answer
127
views
Is there a way to forecast by subgroup without forecasting each subgroup separately?
I am trying to find an appropriate model to forecast the number of applications received at the end of a recruitment cycle based on previous recruitment cycles and the number of applications received ...
6
votes
1
answer
2k
views
Interpretation of binomial GLM (glmer) with interaction and results description
I would like to confirm if I am analysing the results of my model correctly and get some advise if I am missing something!
I conducted the following model to analyse factors that describe the feeding ...
- 377
6
votes
1
answer
2k
views
Interpretation of fixed effect coefficients from GLMs and GLMMs
I am currently interpreting some glm's and glmm's based on distributions with log link functions (gaussian - log, and negative binomial) and have started going in a bit of a loop regarding the ...
6
votes
2
answers
5k
views
How to set up an intercept-only mixed logistic regression in order to test for difference from 50% chance level?
In my experiment, subjects repeatedly had to make a binary choice between A and B, and I want to test if subjects (as a group) differed from 50% chance in preferring A over B. Is there a way to test ...
- 510
6
votes
1
answer
7k
views
Help with zero-inflated generalized linear mixed models with random factor in R
My study has a complicated design and I am not sure if I am modeling my zero-inflated data correctly. I have seed abundances and seedling abundances for 11 species. I have one main "treatment" with ...
- 63
6
votes
1
answer
3k
views
Should I consider time as a fixed or random effect in GLMM?
I am attempting to determine if a type of pesticide is influencing the abundance of a particular species of bird. I have 35 years of data, which was collected along roadside survey routes that are run ...
- 61
6
votes
2
answers
1k
views
Why can't we use top-down methods in forecasting grouped time series?
As I asked in here I was trying to forecast grouped time series with two grouping variables and I find some limitation of hierarchical forecasting methods. In particular, using hts package from R, we ...
- 63
6
votes
1
answer
3k
views
Difference between a random slope/intercept model and an ANCOVA with an interaction?
I attempted to run an ANCOVA with one binary predictor, one continuous outcome, and one continuous covariate. I found that there was heterogeneity of regression slopes and thus I concluded that an ...
6
votes
1
answer
5k
views
How to assess multilevel model assumptions using residual plots
I am not clear as to how to assess if a multilevel model fit using lmer satisfies the assumptions of normality and homoscedasticity?
I have used the following <...
- 123
6
votes
2
answers
3k
views
Correct specification of longitudinal model in lme4
I am trying to fit a multilevel longitudinal model and i have a question regarding how to specify it.
The data consist of about 8k observations collected from about 3k individuals at four time points. ...
- 1,039
6
votes
1
answer
446
views
Expected Fisher information isn't positive definite for truncated normal with heteroskedasticity
This question is about having a non-positive-definite expected Fisher information in a normal model in which observations have different dispersions.
Consider this simple normal model:
$$Y_i \sim N(\...
- 3,800
6
votes
1
answer
307
views
How to interpret my profile likelihood plots (three-level meta-analysis)?
I conducted a three-level meta-analysis to test effects of non-driving related tasks on take-over quality in highly automated driving. When it now comes to interpretation of the results, I struggle to ...
- 71
6
votes
1
answer
2k
views
Model not singular but doesn't converge what could be the reason (lme4 in R)
I'm following up on this great answer regarding running Principal Component Analysis (PCA) to uncover the reason behind lack of convergence and/or singularity for Mixed-Effects models.
My model below ...
- 4,056
6
votes
1
answer
2k
views
How to interpret GLMM results?
My question is related with my previous post Extract variance of the fixed effect in a glmm.
However, in this case I change the model that the GLMM follow.
It follows a log family and as there are ...
- 429
6
votes
1
answer
4k
views
Covariance structures in glmmTMB for temporal autocorrelation
I'm running a zero-inflated, mixed-effects negative binomial model with the glmmTMB package in R.
My current format:
...
- 61
6
votes
1
answer
7k
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 ...
- 163
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
6
votes
1
answer
79
views
Discrete Proportion data -GLMM, regresion beta or multinominal logistic distribution
I have an experiment that have nine treatments consisting of three strains with three different levels of application. Each treatment involves 20 plants, and measurements were taken at three-time ...
6
votes
1
answer
178
views
Role of regression model fit in causal analysis
When analysing causal questions, we use DAGs that give us covariates needed for modelling. But another time we assess model fit to get the best prediction. These two approaches have different purposes ...
- 2,277
6
votes
1
answer
77
views
Doubt regarding mixed modeling format
Say, I have a dataset that looks at how many times my 5 babies chases a cat around the house . I'm trying to estimate 'y' which is the number of times the cat runs one complete round around the house ...
6
votes
2
answers
854
views
How do I interpret the coefficients of a mixed effects multilevel logistic regression differently from regular logistic model?
I am trying to wrap my head around mixed effects multilevel logistic regression. Have a look at my variables:
y: Popularity (0 = Not popular, 1 = Popular)
x1: Extraversion (Continuous)
x2: Teacher ...
- 263
6
votes
1
answer
355
views
BIC in Item Response Theory Models: Using log(N) vs log(N*I) as a weight
In IRT software packages and in the literature it is common to calculate the BIC as
$$
\mathrm{BIC} = -2 \cdot \mathrm{logLik} + \log(N)\mathrm{Npars}
$$
where $N$ is the number of rows in wide ...
- 452
6
votes
1
answer
1k
views
Cumulative counts or counts for Poisson regression
I have a set of data with measurements X1 and X2 across multiple time points, T1, T2 and T3. I would like to conduct a Poisson regression using X1 and X2 on the counts of a phenomenon. An example of ...
- 555
6
votes
1
answer
4k
views
Two-level hierarchical model using time-series cross sectional data?
A question from someone who is fairly new to hierarchical modeling, and I'm looking for the best approach within R, preferably with the package lme4, MCMCpack, or rjags using a BUGS document. I'm ...
- 301
6
votes
3
answers
11k
views
Creating ROC curve for multi-level logistic regression model in R
I used the functions from this link for creating ROC curve for logistic regression model. Since the object produced by glmer in ...
- 3,249
6
votes
1
answer
401
views
How to simulate data for a Gamma glm?
I am wondering about whether there might actually be different ways to simulate data for say a Gamma GLM, which in turn relates to what might be the parametrization that the ...
- 371
6
votes
2
answers
96
views
Appropriate regression model when variables were measured on different subjects?
Imagine the following study design: We have propagated $N$ plants. Each plant produces many seeds. From each plant, $M$ of the seeds are used to measure community composition of bacteria living within ...
- 305
6
votes
1
answer
104
views
Strange result with GLMM (binomial)
I'm analyzing some data, using GLMM and obtain very strange results. The data is of student passing a test, each group of students belong to a different school. So I analyzed the data using ...
- 1,465
6
votes
1
answer
401
views
Proper syntax for coding group level variables in mixed effect model using GLMER
I am running a multilevel log odds regression on a dataset that is at the individual level. Each individual belongs to a district, and there are both individual level variables (which vary by ...
- 63
6
votes
1
answer
375
views
Increasing multicollinearity in multilevel/hierarchical modeling?
I have a linear model with response variable $\textbf{y}$ and explanatory variable matrix $\textbf{X}$ for which coefficients $\textbf{b}$ are physically meaningful and worth estimating:
\begin{...
- 869
6
votes
1
answer
2k
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Is it possible to use LASSO regression with multi-levlel data?
I have real-time monitoring data where participants report on a variety of variables four times per day for a month. Is it possible to use LASSO regression (e.g,. glmnet r package) with this data? I'm ...
- 63
6
votes
3
answers
2k
views
Whether to use a hierarchical linear model
I've been reading through Gelmans book: Data Analysis Using Regression and Multilevel/Hierarchical Models trying to learn more about how to implement hierarchal models. I have a dataset that I think ...
- 323
6
votes
2
answers
5k
views
False discovery rate & q-values: how are q-values to be interpreted when rank of p-values is altered?
I am trying to wrap my head around False Discovery Rate, and its associated q-value; I am new to this technique, but it seems quite promising for my needs.
One sticking point I keep coming across and ...
- 452
6
votes
3
answers
477
views
Estimating correlated parameters with multi-level model
I would like to estimate a multi level model in Stata or R (using lmer) where the first level coefficients are the same for all observations, but the coefficients within observation are correlated.
...
- 958
6
votes
1
answer
68
views
Generalized linear (mixed) model, binomial - help!
I work in biology and I´ve done an experiment exposing an invertebrate to a pesticide at different temperatures. One of my endpoints is hatching success of their eggs. The animals lay clutches of eggs,...
6
votes
1
answer
2k
views
6
votes
1
answer
2k
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 ...
- 141k