All Questions
Tagged with multilevel-analysis logistic
111 questions
0
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1
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35
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Hierarchical logistic regression interaction
looking for some guidance on analyses.
I'm running hierarchical logistic regression models with a cross-level interaction, x and z (both variables are continuous).
Even though the interaction is not ...
3
votes
1
answer
67
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Lack of within-cluster variability
I am working on patients' data. I want to do multilevel logistic regression. The cluster is hospital, exposure variable is treatment (A, B, C), and independent variables include sex, age and others. I ...
- 31
1
vote
1
answer
47
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Multi Level Mixed Models
I have a model in which I collected information from 3 different farms, and on each farm in several different weeks. The weeks are not exactly the same, so week 1 of Farm 1 is not the same moment as ...
0
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0
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54
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Binary logistic/logit regression on multilevel (hierarchical) data (in python)
I'm trying to run a binary logit regression on hierarchical data using python, and I cannot find a way to do that. Any help is appreciated.
The dataset has the following variables:
Accuracy, the ...
1
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1
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53
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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, ...
- 309
2
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1
answer
55
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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 ...
- 309
2
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0
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66
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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 ...
- 171
3
votes
1
answer
48
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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 ...
- 31
1
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0
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28
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How to model a repeated measure logistic regression in r
I am currently trying to come up with a statistical model for my hypothesis. In my experiment there are two conditions (listen/describing). Each condition takes place for 20 seconds per trial. There ...
- 11
0
votes
1
answer
50
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Controlling for variables in multilevel logistic regression modeling
I am new to mixed models and want to calculate a binary mixed model. However, I can't make much sense of the results and am hoping someone can help me out.
So I want to calculate the probability of a ...
1
vote
1
answer
114
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R - How to Address Small Number of Groups in Multilevel Logistic Regression?
I'm implementing a multilevel logistic regression model in R to predict a binary courtroom decision with 8 categorical and 7 numerical predictors. I believe a multilevel model to be appropriate ...
1
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0
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52
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Logistic regression for hierarchical / nested (3 level) data
Research Problem
We are trying to help universities recruit as many students as possible for different projects for a good cause. To be eligible for any project offered by their university, students ...
- 11
1
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0
answers
119
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(Normality) assumptions of logistic multilevel model (glmmTMB)
I have a dataset with patient data in a psychiatric hospital. Some patients had more than one stay, so the observations are not completely independent. I therefore used a multilevel model (in R with ...
- 11
1
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0
answers
50
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Multilevel Bayesian model for Experimental Design with levels in treatment and control groups
Context
I'm designing an experiment and Bayesian analysis to interpret results. I've used Statistical Rethinking as inspiration for model structure.
Suppose I want to study the effects of a sports ...
- 3,520
1
vote
1
answer
35
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Reduced random effect variance by adding more covariates
I'm having a hard time understanding the situation where the variance for the random effect decreased as more predictors were included.
For example, the model below has only two predictors, and its ...
- 375
0
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1
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108
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Can you use Multilevel Modeling (aka Hierarchical Linear Modeling) with Sequential Linear Modeling?
I have a question regarding the use of Multilevel Modeling (aka Hierarchical Linear Modeling) with Sequential Linear Modeling.
I am trying to perform Sequential Linear Modeling (with a binary outcome) ...
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1
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1
answer
216
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Assumptions of a multilevel logistic model
Regarding to another question I'd like to ask the same way but for a quite more specific case.
What are the general assumptions for a logistic multilevel regression?
What are the reasons behind these ...
- 13
1
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0
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279
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Which regression coefficient should be used to calculate Odds ratio? Standardized or unstandardized?
I've run a multilevel logistic regression in R, and I want to calculate the Odds Ratios for the predictors in the model.
R automatically gives the unstandardized regression coefficients for a ...
- 51
6
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5
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3k
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Why do we need Multi-Level Models when we have Logistic Regression?
I am an MBA student taking courses in Statistics.
I attended a seminar hosted by the Statistics faculty in my university in which students present the research they are doing.
The students had data (e....
0
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0
answers
71
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Looking for advice on analysis plan using a mixed linear regression model
I am writing the preregistration for a study and I wanted to check whether my analysis plan can be improved.
Data description
I attached a picture of some random example data to give you a sense of my ...
- 21
0
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0
answers
92
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interpreting assumption tests for multilevel modelling
I have run a multilevel logistic regression model using the glme package in R. I now need to test the assumptions but I am not sure how to interpret the graphs I get, nor whether I'm doing the correct ...
- 51
1
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1
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383
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Missing R Squared and ICC for Multilevel Binary Logistic Regression
I am currently assessing if allocation to a rejection scenario and degree of negative beliefs predicts the odds of engaging in a series of behavioural outcomes (e.g. avoiding the person).
My first IV (...
- 11
0
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0
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22
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What variant of logistic regression is correct here?
Here is my setup:
I have M=200 municipalities who all rank high in corruption
For each municipality, I pick a random sample of ...
- 1
1
vote
1
answer
287
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What is the state of the art for analyzing a mediated moderation in a multilevel logistic regression context?
I had participants in two groups respond to a series of dichotomous decisions. I investigated the interaction between group (level 2) and a level 1 predictor X on the criterion Y. I could confirm this ...
- 113
0
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1
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422
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How to interpret interaction becoming non-significant after removing one non-significant main effect from model?
I am interested in an between-within interaction in a hierarchical logistic regression. I start my analysis with a model including all theoretically relevant predictors, including the between factor A,...
- 113
1
vote
0
answers
32
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Using surgeon-level outcome rate as a predictor of outcome in logistic mixed model regression
I'm working on a study that involves predicting a surgery binary outcome (bailout yes vs. bailout no) in a hospital patient dataset. We wanted to include surgeon-level variables in a mixed model and ...
- 11
2
votes
0
answers
177
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Centering continuous variables in a multilevel logistic regression model [closed]
We are fitting a two-level logistic regression model with continuous variables in Level 1 and no variables in Level 2, except the groups.
We considered only a random intercept in the model, but it is ...
1
vote
1
answer
145
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Advice on modelling longitudinal change of dichotomous dependant variables within clustered data
I'm working with a data set from a multi-school data set and trying to model the relationship between a dichotomous Sleep Status (whether or not they were getting 8 or more hours of sleep per night) ...
- 25
3
votes
0
answers
395
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Best approach for (weakly) informative priors and variable-scaling in hierarchical logistic regression? [closed]
I am a PhD student using logistic regression to investigate mental health epidemiology. Since participants in my cohort study have a diagnosis or not (coded 1 or 0) - I'm using logistic regression to ...
- 108
1
vote
0
answers
50
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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
0
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1
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876
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What are the assumptions that need to be checked for multilevel logistic regression and for multilevel ordinal logistic regression
I am running multilevel models for panel data on a binary outcome (mixed logistics regression) and on a ordinal outcome (mixed ordinal logistic regression).
I am aware that for example with a mixed ...
- 1
1
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0
answers
550
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Why does the intraclass correlation coefficient (ICC) increase as covariates are added to a hierarchical logistic regression model?
I fit three Bayesian binary multilevel logistic regression models. Schematically they look like this:
...
- 409
2
votes
1
answer
582
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Is there a minimum number of observations needed to justify the use of random slopes in a logistic regression model?
I have a mixed-effects logistic regression model with 584 observations, which models the outcome of a variable linguistic phenomenon. There are three predictor variables and I I used random intercepts ...
- 409
0
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1
answer
3k
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Residual diagnostics in DHARMa for multilevel logistic regression
I'm running a multilevel logistic regression, and have been trying to look at residual diagnostics using the DHARMa package. My data is copy-pastable from here and the following code should run ...
3
votes
1
answer
229
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Implications for sample size of multilevel/mixed-effects model when level 1 units are participant decisions and level 2 units are participants
I am planning a study that will use a hierarchical design. The study has participants engage in a decision-making task, wherein they make 40-50 decisions between 'Choice A' and 'Choice B' (I won't ...
- 439
1
vote
1
answer
589
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glmertree to fit logistic regression with two-column y
With both glm and glmer, if I wanted to fit a proportion, I could do it as
either:
...
1
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0
answers
138
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What is a sufficient sample size for a logisitic multilevel (three-level) analysis?
I have an exploratory research question for which I use a repeated measure design with 3 levels:
level 1 = 3 measurement occasions per day
level 2 = day
level 3 = participan
To keep the effort for ...
- 11
2
votes
1
answer
103
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How to fit the correct multilevel (logistic) regression?
I want to study the link between hospital competition and mortality. The competition a hospital faces is measured by the Herfindalh-Hirschman index (HHI). So I want to know if a hospital's HHI is ...
- 939
4
votes
1
answer
208
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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 ...
- 939
-1
votes
1
answer
2k
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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 ...
1
vote
0
answers
28
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Help with MLM specification (data clustered by group and year) lme4 R
I have a dataset structured like so:
...
- 11
1
vote
1
answer
566
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three-level logit regression with random slopes
I am trying to find the correct code for a three-level multivariate logit regression. I have protest participation, education level, and income data from a number of countries. Data are also divided ...
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2
votes
1
answer
166
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Choosing a regression model for proportion data at the school level
I am working on a dataset where I have the percentage of students who passed at a test for each 189 schools in my sample. The data is aggregated, so I have the total number of student who sat the test ...
- 21
2
votes
0
answers
133
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Why do Bayesian hierarchical models converge where frequentist models do not?
I am analysing an experiment looking at abstinence rates among participants in a clinical drug and alcohol trial. There were two groups, those who received the new treatment and those who received ...
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1
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0
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39
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How can I test the proportion of "significant" effects in a logistic mixed effects model?
I have a binary outcome variable $Y \in {0, 1}$ in $N$ groups that I assume to be generated by the logistic process
$$
P(y_{ij} = 1) = \frac{1}{1 + \text{exp}[-(\underline \beta_{j0} + \underline \...
- 71
1
vote
0
answers
97
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Do I need a multilevel model with no level-1 explanatory variable? (logistic regression)
Short version:
I am fairly new to multilevel modelling and would like to avoid it. My question is basically if I can leave it aside given the nature of my data and the goals of my analysis.
My ...
- 11
1
vote
1
answer
442
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Using a multi-level model when some variables are clustered but majority is not and there are plenty of clusters?
I use an example to illustrate my question.
I have a model that explains choice of low fat vs full fat milk, that was actually bought in a store. We model it with a binary logistic regression.
The ...
- 235
1
vote
1
answer
375
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Multilevel binary logistic regression assumptions
I am struggling to work out the assumptions of hierarchical binary logistic regression, to test whether my data is suitable for such an analysis.
My data is repeated measures (each participant ID ...
0
votes
1
answer
37
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Help Selecting Statistical Test
I am looking for advice on how to analyze some experimental data.
My DV is a binary response variable - yes or no (coded as 1 and 0).
Usually when I run experiments I fully cross all conditions ...
1
vote
1
answer
217
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Use a multilevel logistic regression and cross validation
I want to use a multilevel logistic regression for a double purpose, estimating the value of coefficients to explain a phenomenon. At the same time, I want to split the data through cross-validation ...
