All Questions
Tagged with multilevel-analysis interpretation
30 questions
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
2
votes
0
answers
38
views
Can I conclude this from my random effects model?
I'm currently performing a random slope model to figure out whether the hierarchical factor (categorical: e.g., school A, school B ...) is biasing my results. I've used the following model/code in R:
...
- 21
2
votes
1
answer
688
views
The correct interpretating a three-way interaction in a linear mixed model analysis
Context
The purpose of this analysis is to examine sex differences in Bath Ankylosing Spondylitis Functional Index (BASFI) scores in Axial spondyloarthritis (axSpA) patients who are starting their ...
- 315
0
votes
0
answers
20
views
How to model multi-level data to interpret features of individuals?
I am currently very thorn about how to best proceed on the problem I am working on. The data consists of observations (y) of the effect of As on Bs. In particular, y is a percentage difference so the ...
3
votes
1
answer
1k
views
Meta Analysis in R (metafor): How to interpret a multi-level mixed effects model with intercept and without intercept?
Dears,
I am having trouble making sense of two MLMEs I did using rma.mv(). I am using a factor variable with 4 levels as a moderator. The two outputs (once with ...
- 43
1
vote
1
answer
538
views
How to interpret hierarchical regression output that has insignificant IV in step 2, but still shows significant F
I'm working through a 4-step hierarchical regression where the first step is to add grouping variables (student standing, gender, & previous experience) and the 2nd step as adding a psychological ...
Nibuz_Ertived
2
votes
1
answer
39
views
Interpreting unintuitive fixed effects sizes in linear mixed effects models
We are working on the analysis of an online behavioral experiment in which participants had to solve problems presented in two different linguistic tenses. One of them was ...
- 23
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
1
vote
0
answers
50
views
Interpretation of predicted probabilities of multi-level logit model when "integrating over the random effects"
Let's say I run a single-level logit model of "being depressed", as a function of age (in years) and opiate use (binary). The model looks like this
$Pr(Y_i=1)=\frac{exp(\beta_0+\beta_1Age_i+\...
- 6,020
5
votes
1
answer
749
views
Should I remove random intercepts from my model?
I have collected some data on response times (Y) under two varying conditions (X1 and X2). The conditions are continuous variables, although I set them to fixed values of 1,2,3,4 and 5.
I have 10 ...
- 409
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
0
votes
1
answer
174
views
Why do results differ with and without offset in Poisson regression?
I have a dataset with counts of preterm births for five years by county. I am running analyses to see whether contaminant water concentration levels for each county for each year predict preterm ...
- 11
5
votes
1
answer
548
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 ...
- 235
0
votes
1
answer
55
views
Interpretation when Information Criteria and F-Test Disagree
I used SPSS (v. 25) conducted a pair of nested multtlevel models (aka linear mixed models) where the outcome criterion is itself also nested within participants. I followed Singer and Willett's (2003) ...
- 27
1
vote
0
answers
29
views
Interpreting a Bayesian Hierarchical model with a center and a difference parameter
Suppose we have a Bayesian Model where the data level specification looks like
$$
Y_i \sim Bern(\pi) \\
X_i \sim LogNormal\Big( \alpha_{S_i} + \left[\pi \cdot Y_{S_i} - (1-\pi) \cdot Y_{S_i}\right]\...
- 4,260
0
votes
1
answer
162
views
Interpretation question about between-subjects effects in multilevel modeling
Specific question that (of course) comes from a reviewer. In multilevel models with:
Level2=individuals
Level1=within-persons
Is it fair to say that, since these models explicitly estimate Level 2 ...
- 3
0
votes
1
answer
72
views
1
vote
1
answer
179
views
How to manage a variable collected at various level in a machine learning model based on nested hierarchical data?
I'm trying to use machine learning to model the risk of healthcare-associated infections (HAI) for patients in a number of hospitals. I have variables both at the patient, ward and hospital level.
...
- 2,939
0
votes
1
answer
232
views
Multilevel analysis - interpretation not significant at level 1
I'm doing a multilevel analysis for the first time for my master thesis.
The goal of my study was to create behaviour change through an intervention. Participants are measured for behaviour at 3 ...
- 1
0
votes
0
answers
2k
views
How to Interpret the result of generalized linear mixed model?
I ran a generalized linear mixed model using lmer in R, and I'm struggling how to interpret the result. The response variable is a result of 25 consecutive binary choices. The point where I'm stuck is:...
2
votes
1
answer
905
views
Interpreting a three-way interaction in a multilevel growth model
Background
I have the following multilevel (mixed effects) growth model:
$$y_{it} =\beta_{0} + \beta_{1}Time_{it} + \beta_{2}Time^2_{it} + \beta_{3}GHP_{i} + \beta_4Baseline_{i} + \beta_5(Time_{it}*...
- 581
1
vote
0
answers
1k
views
Negative and not significant intercept in multilevel model [closed]
the objective of my work is to estimate whether policies can increase men's time investment in housework. In order to estimate whether the regulation of normal weekly working hours affects men's time ...
- 21
2
votes
1
answer
2k
views
How to interpret random intercept "BLUP" from the sjPlot package?
I am using the sjPlot package to estimate my multilevel model and I am loving it. However, I am a bit confused by the output of the random intercept.
Background:
My dependent variable is on a scale ...
- 118
1
vote
1
answer
4k
views
Interpretation hierarchical regression
I'm running hierarchical regression to determine whether or not a number of independent variables are able to explain a dependent variable. I have following models:
Model 1: only controlvariables
...
- 101
5
votes
0
answers
2k
views
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
2
votes
1
answer
104
views
When fitting a GLMM, is the predicted value for any success or all successes or what?
I am relatively new to multilevel modeling and have just been given an assignment that uses a generalized linear mixed effects model. The outcome is smoking status (1=yes, 0=no) measured at three ...
- 21
1
vote
0
answers
897
views
Hierarchical Regression Moderator Analysis
I ran a 2-block hierarchical regression to test for moderation. In the first block I entered the centered IV and centered moderator variable (MV) and in the second block I entered my centered ...
- 11
4
votes
1
answer
2k
views
Multilevel logistic regression with a random slope(s)
I would like to specify a two-level logistic regression model with random intercept and random slope.
Dependent variable: hospitalization (1) or no-hospitalization (0).
Independent variables: age, ...
- 153
0
votes
1
answer
588
views
Increase of odds ratio in a non-significant predictor
I ran a hierarchical logistic regression with 2 blocks/predictors:
I found out that block 1 is not a significant predictor, but block 2 is. Still: the odds ratio for block 1 is MUCH higher (2.90) ...
- 25
3
votes
2
answers
2k
views
How do I setup a model with hierarchical structure using lmer in R?
I am trying to isolate the important predictors for my response variable "Y". I know that "TL" (which is an individual level predictor) affects "Y", and now I want to determine if adding the site ...
- 53