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].

Filter by
Sorted by
Tagged with
2 votes
1 answer
12 views

How to code for a mulitgroup analysis concerning two catagorical variables

I have a question on syntax for Mplus. I am running a multivariate latent growth curve with 7 repeated measures, variables X and Y (diagram attached). I also have two grouping variables, sex and ...
EmH's user avatar
  • 89
0 votes
1 answer
20 views

Random effect variance with or without fixed-effects intercept

I'm fitting some hierarchical models in R using lmer, and am trying to understand why the results change as they do when I either include or exclude a fixed-effects ...
neurobot's user avatar
2 votes
1 answer
35 views

Multilevel model with random subset of conditions per participant

I have a repeated measures experiment with 5 factors each with 3 different levels. I'm trying to figure out a way to reduce the demand on participants by making them not have to sit through every ...
Andrew Thomas's user avatar
1 vote
0 answers
35 views

Understanding equatiomatic output

I have fit a lmer model as follows: ...
Rabin KC's user avatar
3 votes
1 answer
84 views

How to add interaction and covariates to linear mixed effects model in R

I have some data ($x$ and $y$) collected over multiple days for multiple people. I want to test whether the contemporaneous associations between $x$ and $y$ (measured daily) is stronger depending on ...
Lavdoy's user avatar
  • 31
1 vote
0 answers
13 views

How to perform multilevel moderated mediation analysis with {mediate}

I'm attempted to run a multilevel moderated mediation analysis in R using the mediate package. Some details on my sample: I have an experimentally manipulated ...
Ethan Milne's user avatar
0 votes
0 answers
19 views

Single or Multiple Bivariate analysis?

For the data structure, we are fitting the multilevel model to the data. Before fitting the model, we are eager to do bivariate analysis so that we can keep those independent variables in the ...
user232597's user avatar
2 votes
1 answer
56 views

Advice on optimal random-effects structure for not fully crossed repeated-measures design?

I have a study that is designed such that it seems to straddle a within- and between-subject design. I posted about this previously here, but at that stage I was hoping for a simple ANOVA-like ...
nostatisfaction's user avatar
3 votes
2 answers
37 views

Better understanding of "within" and "between" in multilevel models

In my work I mostly use latent variable modeling, but due to a recent project, I now have to also use a multilevel model. I have a situation where latent constructs of geography knowledge (measured ...
J. Doe's user avatar
  • 317
0 votes
0 answers
26 views

Conducting a moderated multilevel mediation with more than two levels in R

I'm trying to conduct a moderated multilevel mediation model in R, but I'm still a pretty junior graduate student and I've only ever done mediation with lavaan. My outcome variable is cortisol, for ...
calexico's user avatar
1 vote
1 answer
22 views

Getting a very big relative risk ratio value

We have fitted a multilevel multinomial logistic regression model to our data. We have obtained relative risk ratios(RRR). For most of the independent variables RRR have usual values, like 0.49, 0.78, ...
user232597's user avatar
0 votes
0 answers
40 views

Meta-analysis: estimating partial correlation coefficients using estimates from multi-level analyses

I would be very grateful if someone could offer some ideas or point to relevant literature on the calculation of partial correlation coefficients (PCCs) using estimates from multi-level analyses. ...
Mugen's user avatar
  • 1
2 votes
0 answers
55 views

Power sizing when sampling from a group with known subgroups

I need to do a power analysis of a group that is composed of three subgroups. The measurements to sample are difference measurements between two dogs of the same breed rated side by side. Dogs are ...
Estimate the estimators's user avatar
0 votes
0 answers
18 views

How to select a proper prior to control the time dependent structure of variable?

I am new in analyzing RCT data and not familiar with the techniques that are always used in RCT analysis. I am analyzing a dataset of a study: An RCT study with 50 participants; the data was collected ...
doraemon's user avatar
  • 198
1 vote
1 answer
51 views

Multilevel Modeling and Alternatives for Repeated Measures Design

I am conducting a study on the effect of different characteristics of urban space on human physiological response. The study is a "repeated measures" design. For this example, each of 5 ...
Mark S.'s user avatar
  • 21
2 votes
2 answers
113 views

Mixed-effects model of nested time series [closed]

I have time series data for a variable from different climate models, each with multiple runs using different initial conditions (ensemble members). A small subset of the data to see how its laid out (...
Elio Campitelli's user avatar
0 votes
0 answers
13 views

Ensemble, merge or combine multiple lmertree objects

Working with the PISA data, which includes multiple achievement scores (plausible values) for each participant, I would like to run the same lmertree and ensemble ...
Burak Aydin's user avatar
1 vote
0 answers
15 views

Zero inflated and right skewed dependent variable – is the Tweedie distribution a good solution?

We are conducting a variance decomposition using a hierarchical linear random effects Bayesian model to investigate the variance in a DV that is affected by three nested layers. Because the DV is ...
james_westfield's user avatar
1 vote
0 answers
26 views

Width of Confidence Intervals for Variance Estimates in Contrast to Point Estimates

We are conducting a variance decomposition using a hierarchical linear random effects Bayesian model to investigate the variance in a DV that is affected by three nested layers. We estimate credible (...
james_westfield's user avatar
3 votes
1 answer
68 views

Specific group effects (coefficients) in mixed-effect modeling in R (lmer)

Just assume a situation like this: "A" is the independent variable, which is as both between- and within-level. "B" is another independent variable, which is only as within-level. &...
Enmi's user avatar
  • 33
2 votes
1 answer
43 views

Is it reasonable/possible to use pre-scores as predictors of change?

In change analyses (of any variable, from pre to post) we usually controll for the pre-score, as it may affect the rate of change. However, what if I am especially interested in the effect of the pre ...
user405152's user avatar
0 votes
0 answers
36 views

Interpreting results from a glmm (lmer) with multilevel and interaction fixed variables

I am running my GLMMs on R to test whether the effect of breed on the acoustic parameters of meows is dependent on sex levels (sex*breed) and to test whether the ...
Alice 's user avatar
2 votes
1 answer
47 views

Comparing statistical measurements of several countries

In a study, an outcome variable has three categories. There are several factors in the study. We are determining how these factors influence the outcome variable.We have fitted multiple logistic ...
user232597's user avatar
2 votes
1 answer
65 views

Subsamples of multilevel data

We have the PISA data with a multi-level structure (student - school - level). The schools were selected randomly. In this case it is well known to use multilevel methods. Considering subsamples, we ...
David Gutiérrez Rubio's user avatar
8 votes
1 answer
59 views

MLM / HLM Equal sample sizes needed between groups?

I am working on analyzing a dataset from a diary study (6–14 repeated measures per participant). The sample I have consists of 2 groups (1 with expertise, 1 without) that are thought to differ on many ...
r-ks's user avatar
  • 113
2 votes
0 answers
42 views

Multilevel Marginal Structural Models and Centering Predictors

I have read that centering the values of predictors (subtracting the individual, $i$, value from the group mean, $j$, value or the grand mean) in a multilevel models aids in the interpretability of ...
Brian Lookabaugh's user avatar
1 vote
1 answer
56 views

Calculating standardised regression coefficients from GLMER model

I have three separate glmer models investigating the individual and household-level risk factors of malaria infection in three different spatial locations: 1) outside the forest, 2) at the forest ...
Trypanosoma's user avatar
1 vote
0 answers
41 views

Multilevel Regression and Poststratification (MRP) weighting in the opposite direction to Poststratification alone

We are using MRP to derive test norms for an IQ test (Culture Fair Test, CFT) based on the TwinLife data. We adjust for age, sex, education, and migration background. Although a probability sample, ...
balout's user avatar
  • 11
0 votes
0 answers
22 views

Using sample at lower hierarchical level (products) to draw inferences about a higher hierarchical level (companies)

I have a conceptual question about whether we can use a random sample of products to draw inferences about companies. More generally, I think this would extend to sampling hierarchical data, where we ...
jdcrossval's user avatar
0 votes
0 answers
35 views

Calculate the average marginal effect (AME) in the multilevel regression with glmmTMB package

I am writing this message because I want to calculate the average marginal effects (AME) in order to be able to interpret an interaction resulting from a multilevel regression. However, I am finding ...
Jules's user avatar
  • 11
1 vote
0 answers
32 views

Multilevel model: Contradictory results between multilevel model with interactions and segmented model

I am working on a research paper exploring the differential effect (or interaction) of financialization on the housing conditions of the population according to tenure status. For this purpose, I ...
Jules's user avatar
  • 11
4 votes
1 answer
103 views

What it means to model the residuals of a multilevel model?

I have a highly skewed dataset. But, my MODEL of choice below shows drastically improved, normally distributed residuals (and predicted values) compared to other models whose residuals are not modeled....
Simon Harmel's user avatar
3 votes
1 answer
54 views

When should grouping variables interact in a mixed-effects model?

I was reading this post which is relevant to a research project I'm working on now. I think that I understand the difference between crossed and nested random effects, e.g. as described here. The ...
wzbillings's user avatar
3 votes
1 answer
68 views

Mixed effect models for survival analysis

When performing survival analysis with mixed models I've usually used random intercept or random intercept and random slopes models with these codes in R: Random intercept: ...
Claudio Laudani's user avatar
0 votes
0 answers
17 views

How to interpret predicted intraindividual variance (residual variance)? [duplicate]

Background I'm working on a project on modeling/understanding the intraindividual variance of a repeat measurement. To do this, I'm following a tutorial set out by Dr. Nilam Ram that can be found here ...
Brian Patchett's user avatar
1 vote
0 answers
64 views

Mixed design experiment: median reduction or linear mixed model?

I collected data from an acoustic localization experiment with a mixed-design, where the factors are populations (one with hearing devices (HA) and one with cochlear implants (CI)), and conditions, ...
Andrea Gulli's user avatar
2 votes
0 answers
52 views

C-statistic and measuring the contextual effect in multilevel logistic regression

I have a two-level logistic regression model where the outcome is "InfectedqPCR" (Plasmodium-infected as determined by qPCR) at the individual level. I have a range of individual- and ...
Trypanosoma's user avatar
0 votes
0 answers
36 views

Suitability of multilevel poisson regression model

I am planning to fit a statistical model to a dataset in which there are details about bird-farms from various geographic locations, 7 environmental variables, egg_hatching years, and eggs_hatched. An ...
Rahul's user avatar
  • 1
2 votes
0 answers
23 views

High Standard deviation for regression coefficient in multilevel model with random slopes compared to fixed slopes

Recently, I compared two multilevel models of the same data: One with fixed slopes: R Code: ...
C K's user avatar
  • 51
0 votes
0 answers
11 views

Multi-level meta: do I include a measure of precision in subgroup analysis model?

In a meta-regression model, a precision measure (SE or SE^2) is often included in the model along with covariates. Is the same true for subgroup analysis in a multi-level analysis wherein moderators ...
Daniel's user avatar
  • 1
0 votes
1 answer
75 views

Including covariates in a multivariate multi-level meta-analysis

I am carrying out a multivariate multi-level meta-analysis, and I have a question regarding including moderator variables in the context of publication bias. Doucouliagos and Stanley (2009) recommend ...
Daniel's user avatar
  • 1
1 vote
1 answer
36 views

Modelling 3-level MLM of longitudinal data in R

I have two questions regarding modeling a 3-level multilevel model in R. I have a dataset of different variables that were assessed 4x as part of a longitudinal study. At each of the four assessments ...
Eve's user avatar
  • 11
0 votes
0 answers
19 views

Modelling 3-level MLM of longitudinal data in R

I have two questions regarding modeling a 3-level multilevel model in R. I have a dataset of different variables that were assessed 4x as part of a longitudinal study. At each of the four assessments ...
Eve's user avatar
  • 11
1 vote
0 answers
36 views

Interpretation of Multilevel Mediation

I am attempting to perform a multilevel mediation and found this page online with an example: https://stats.oarc.ucla.edu/r/faq/how-can-i-perform-mediation-with-multilevel-data-method-2/ It follows a ...
Paul's user avatar
  • 56
0 votes
0 answers
42 views

Interpretation of an interaction effect (ratio of odds ratios) when using effect coding

I ran a multilevel logistic regression model using function glmer from R package lme4. All of my predictors are binary and I have used effect coding, i.e., coding -...
Michael Krah's user avatar
2 votes
1 answer
43 views

Interpretation of random effects in mixed model with glmer()

I'm working on a final project and need to estimate a multilevel logistic model for analyzing dropout rates in higher education in a specific region. The model has three levels, where intercepts vary ...
gustavobrp's user avatar
2 votes
1 answer
38 views

Multi-level modeling as a statistical criterion

I found Doordashe's article about conducting switchback experiments. In their article they use multi-level modeling instead of statistical criterions, which are usually used in A/B testing. They ...
Соня Бондарь's user avatar
0 votes
0 answers
17 views

How to model clustered data structure association when all clusters are observed at the same time?

I have data from many recipes I made that describes how different ingredients subgroups grouped in different parent categories (sweet, sour, bitter, umami ) work together to ultimately lead to scores ...
Estimate the estimators's user avatar
2 votes
1 answer
24 views

VPC for a three-level logistic regression

I am building a mixed effects logistic regression model to explore whether or not someone is diagnosed late with a specific infectious disease. My outcome is late diagnosis (yes/no). My data includes ...
jaspy87's user avatar
  • 21
7 votes
1 answer
432 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 ...
Nate's user avatar
  • 1,469

1
2 3 4 5
38