Questions tagged [multilevel-analysis]
Statistical analysis of datasets comprising several levels of hierarchy (e.g., students nested in classes nested in schools or hierarchical forecasting). For questions about mixed models use [mixed-model] tag. For nested random effects, use [nested-data].
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Interpreting variance components in a multi-level meta regression in r using Metafor
I have conducted a multi-level (to account for trial and study levels) meta regression in r using Metafor. There is 20 effects derived from 11 papers. The model seems fine apart from the attached ...
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7 views
Ok to repeat same measurement in different column and different row of design matrix for multilevel model?
I have a process that unfolds in time for each participant like this:
measurement1 -> event1 -> measurement2 -> event2 -> measurement3
Each of these are continuous variables (measurements ...
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1answer
18 views
Redundant Parameters in Cross-Level Interaction: Mixed Modeling
I'm using SPSS to run a Mixed Model with two categorical (factor) predictors with an interaction between the two predictors. I get the following Estimates of Fixed Effects:
In the interaction I am ...
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27 views
Multi level meta-analysis model
I'm working on meta-analysis in the agricultural sciences.
I have four groups a, b, c, d which are nested within each study.
One paper can have multiple studies and each study may have data from ...
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1answer
29 views
Approximation in hierarchical model
Consider a simple Bayesian hierarchical model:
$y | \theta \sim P(y | \theta)$
$\theta | \phi \sim P(\theta | \phi)$
$\phi \sim P(\phi)$
I'm interested in drawing from the posterior distribution of $\...
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1answer
15 views
Does it change anything in a multilevel model when the predictor is a higher-level variable?
I am working on a project where I have to study the link between hospital competition and mortality (but also the duration of hospital stays). More precisely I want to determine whether the more a ...
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1answer
49 views
ANOVA with missing cells and multi-level analysis
I'm about to analyse some data (hypothesis testing) and would like some feedback on my approach as I have never seen this situation (missing cells in an ANOVA-like table). I would also like to know if ...
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19 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 ...
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Weights in multi-level models
I really hope that this is the right place to ask my question and that it hasn't been asked yet - otherwise please let me know.
I am currently running a multi-level regression model with a cross-level ...
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1answer
42 views
Between- and within-person level effects when using multilevel modelling for longitudinal data in R
I’m using nlme package in R for analysing longitudinal data. The aim is to understand if changes in need satisfaction (TNS) and ...
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0answers
6 views
Group level distribution for positive parameters in Bayesian multilevel models
I am doing a lot of modeling with models that require some parameters to be positive by design. However, I am struggling to figure out which approach works best when I try to use multilevel modeling ...
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How to explain a multilevel model bias towards one of the levels?
My multilevel model's 2 levels consist of land surface images and meteorological readings from different places. The readings are level 2, with 7 variables and 1 observation per group. The images are ...
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1answer
20 views
lme4: Three-Level Autoregressive Model - Random Effects
I would like to fit a three level autoregressive model in lme4 to account for my longitudinal experience sampling data (beeps nested in days, nested in persons).
Several resources suggest to account ...
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20 views
Modeling repeated cross sectional clustered data
I have repeated cross sectional data from convenience samples of students nested in schools nested in districts. I have data on student-level behavioral outcomes (binary) and school-level program ...
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4answers
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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 ...
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14 views
Creating a 2-level mixed model in SPSS to find predictors nested within subjects
I'm working with longitudinal data, and am using the mixed models function ins SPSS to look for predictors (level-1) nested within individuals (level-2).
If I add the participant ID as "subject&...
3
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1answer
49 views
Book recomendation introducing multilevel models for a pure mathematician
Is there a good book on Multilevel models (random intercept, random slope, fixed effects, etc.) written for mathematicians which treat the theory rigorously?
My background is essentially is in the ...
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12 views
Random assignment but statistically significant differences at baseline
I have an experiment that randomizes a participant to 1 of 3 conditions. Outcome is heart rate over a period of time (measured at 1-minute averages). Despite randomization, there is statistically ...
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7 views
What is a “batch” of coefficients in Bayesian multilevel modeling?
I’m well acquainted with frequentist approaches for multilevel models (i.e. mixed/random effects models with random intercepts or slopes), and empirical Bayes estimation, but I’m trying to get ...
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1answer
27 views
Standard error in multi-level models vs. non-multi-level models
Gelman & Hill (pp. 252-259) discuss "no-pooling" (single-level), and "partial-pooling regression" (multi-level) with no predictor ($section~ 12.2$).
In almost all mixed-effects ...
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14 views
Hierarchical model with a different set of covariates by group
I'd appreciate any good reference material on specifying a hierarchical model with a different set of covariates by group. Textbooks usually reference varying intercepts and slopes, but in my real ...
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0answers
20 views
suggestion for ordinal logistic regression or CLMM
I want to use a ordinal logistic regression that works with 2 random variables. I know that POLR and CLM don't work for multilevel regression and I am trying CLMM.
I am evaluating how much the method ...
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0answers
26 views
Multilevel hierarchical simulation? What model to use?
The problem: I have a dataset that I think could be deemed hierarchical. Assume that there are 1-100 ids, which all can have anywhere from 1-3 sub_ids. Both the top ids can have specific features that ...
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1answer
24 views
Fixed effect turns insignificant when including random effect - Multilevel
I have a data set from a diary study in which stress was assessed for 30 days. I want to build multilevel regressions (level 1: measurements, level 2: persons) to investigate the effect of different ...
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How to model repeated measurements with the same outcome in a Bayesian framework?
Can't think of a more accurate title, so I'll illustrate the problem with an example.
I want to record temperature using cheap noisy sensors. I also have recordings from a gold-standard reference ...
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2answers
53 views
Follow-up: Complete-pooling, no-pooling, and partial-pooling regression in R
This great answer demonstrates the concepts of "complete-pooling regression", "no-pooling regression", and "partial-pooling regression" (3 concepts) using simulated data ...
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1answer
24 views
How to interpret main effect with two interaction terms?
I have three variables in a multilevel model:
Relationship Status (0 = single, 1 = not single)
Living Arrangement (0 = alone, 1 ...
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Diary study: Should I model time with very unbalanced time-points? (Multilevel analysis)
I have a data set from a diary study in which daily stress during the current pandemic was assessed for 30 days. However, participants began their diary period at different time points, leading to an ...
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1answer
35 views
Are priors in Bayesian inference similar to levels in mixed-effects models?
I often see a frequentist multi-level model (MLM) structure is defined like so (made up parameters):
$$ \theta_i \sim \mathcal{N}(10, 2.5) $$
$$y_{i,j} \sim \mathcal{N}(\theta_i, 0.5) $$
But this is ...
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1answer
14 views
How to interpret interaction in the absence of main effect? Multilevel Modeling
What is the substantive interpretation of an interaction in the absence of a main effect? Statistically I understand that the interaction modifies the main effect, but how to interpret this from a ...
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1answer
32 views
Hierarchical modelling in Python with statsmodels
I have a dataset with random effects at different hierarchies and now I want to analyze how they influence my target variable. Somehow I'm looking into statsmodels ...
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0answers
30 views
Comparing absolute rather than relative (percent) change in a negative binomial mixed effects longitudinal model
My question is:
Is there any multi-level method or library, preferably in R, that will predict a negative binomial outcome from multiple covariates and a “moderator," and then report on the ...
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0answers
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How do I get merTools/ lme4 to report p values for multiply imputed data? [migrated]
I am using the R packages lme4, merTools and Amelia to run a multi-level model with multiply imputed data. The merTools function "print.summary.merModList" gives the model results, including ...
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17 views
Leave random effects out when correlated with fixed effects?
Is it appropriate (or not) to leave a random intercept out of a model if the random intercept acts as a proxy for multiple fixed effects that are being included in the model?
I have been given data on ...
4
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1answer
62 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
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1answer
108 views
Demonstrating complete-pooling, no-pooling, and partial-pooling regression in R
Gelman & Hill (pp. 255-259) demonstrate in R how to achieve a "complete-pooling regression", "no-pooling regression", and "partial-...
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1answer
32 views
A figure or narrative to compare multi-level models and fixed-effects ANOVAs
TL;DR: What figure or narrative can represent a fixed-effect ANOVA if we represent $complete~pooling$, $no~pooling$, and multi-level (partial pooling) models using the following figures (and ...
3
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1answer
32 views
Are time points nested in students or crossed in a longitudinal multi-level model
I often hear that in a longitudinal multi-level analysis, time points (as a fixed factor) are "nested" within students (e.g., just search the word $nest$ in this paper).
However, this great ...
3
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1answer
40 views
Help understand data structure and appropriate model (hierarchial data wtih repeated measures)
I have credit card transaction data, that I will describe with a relationship diagram.
There are thousands of records, which are tied to a credit card, tied to a customer. Each customer can have 1-2 ...
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1answer
42 views
How multi-level models account for correlation and what kinds of correlations?
Multi-level models are often shown using figures such as below. These pictures say that observed data at the lowest level (BLUE TRIANGLES) come from some independent populations (BLUE CURVES). But the ...
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Multilevel model with subset of compositional data
I am working on an analysis where I am trying to predict BMI with a subset of microbiota data. Microbiota data is inherently compositional. I will be using a multilevel linear model. For the analysis, ...
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How to run a Hierarchical multiple linear regression for impression management?
Thank you for your help!
I am looking to run a Hierarchical multiple linear regression as part of my study. I am looking to see what if any impact impression management has on self report behaviours ...
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1answer
34 views
Hierarchical logistic regression package in R
I'm working on a logistic regression model; the purpose of the analysis is to identify factors that influence use of an app - the DV being use/no use, and IVs being a couple of numerical and ...
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1answer
17 views
Gain scores as an outcome in HLM?
I'm analyzing data from a single-group, pre-post design, trying to see if student beliefs change after an intervention. Students are nested in classrooms, and there is a significant amount of ...
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0answers
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Coefficients for all levels of a categorical factor unchanged in lmer after adding variables
I was sent over here from stack overflow here:
https://stackoverflow.com/questions/62635123/coefficients-for-all-levels-of-a-categorical-factor-unchanged-in-lmer-after-addi
(sorry for posting there ...
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1answer
54 views
brms intercept only model runs very slow
I am trying to learn brms package for multilevel modeling. A reproducible code is as below:
...
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1answer
24 views
summarize extent of pooling or shrinkage in multilevel models estimated with lmer()
I am using lmer() in the "lme4" package to estimate multilevel models. The models include random intercepts for each group in my data. To fix ideas, here ...
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1answer
101 views
Mixed Effects Model: Writing out and interpreting coefficients on Level 1, 2, and 3 Models
Question: Have I written formulas that convey the correct mathematical representation for my three-level model? Is my written interpretation of the coefficients in the equations correct?
I have a ...
5
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1answer
40 views
Intercept interpretation in multi-level model when first-level predictor discrete
This is the experimental setup:
1 dependent variable (discrete, 4 levels) and
3 Independent variables:
Time, measured within subject, 5 discrete levels
Covariate, measured within subject, 5 discrete ...
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0answers
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Mixed-effects models with lasso penalty and ridge penalty in R [closed]
I am using the PISA 2015 data and trying to run a mixed-effects ridge and lasso regression model Schools will be included as a random effect, and student-level (e.g. motivation, socioeconomic status, ...
