Questions tagged [marginal-model]

A marginal model estimates population averages, in contrast to a subject-specific model that estimates an expected value conditional on a subject's attributes. In a linear model context, these are the same, but they differ for nonlinear models. The GEE is the most salient marginal model.

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Summary Statistics for sparse, imbalanced, observational data

I am trying to find a good summary statistic (next step is going to be inference) for my problem. I have observational data that is images for patients (factor1) with different conditions (factor2) ...
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How to handle intermittent missing visits in marginal structural model?

The reference papers for marginal structural models only talked about handling monotone censoring using IPCW. How to deal with intermittent missing visits? Does it make sense to use available visits ...
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Marginal predictions from a conditional survival model

I’m looking at making predictions of baseline and treated survival from a parametric survival curve that are unbiased. I have a matched sample to try to control for observed confounding and wanted to ...
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A Bayesian marginal structural model (IPW) in a single model

Inspired by Richard McElreath's "Full Luxury Bayes" in his Statistical Rethinking course, I wanted to implement a "Full Luxury Bayesian Marginal Structural Model". Briefly: MSMs ...
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What does marginalizing a model mean?

I'm reading the following chapter on Partial Dependence plots, from the book Interpretable Machine Learning. In this chapter the author states that you calculate the partial dependence of a model on a ...
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As a researcher dealing with randomized trial, should I use GEE or a GLMM? [closed]

I'm sorry, I searched all topics on StackExchange and cannot still get the difference between marginal and conditional model. All answers tell me the same by showing averaged non-linear curves, which ...
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Marginal structural model with time-varying exposure only (time-fixed covariates)

We have survival data in counting process form (max 2 records per patient), relating to a time-varying treatment (some patients stay on a low dose of the drug the entire time under observation, some ...
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Nonlinear effects of time-varying covariates from marginal rates model

This is a followup analysis on this post, inspired by the comments from @EdM. I fitted a marginal rates model (Lin, Wei, Yang, & Ying, 2002) on recurrent event data but don't know how to include ...
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Marginal structural model - help with some concepts

I'm trying to gain some (deeper) understanding of MSM's - what exactly they are and when they might be appropriate to use. Are my thoughts on the following correct (please feel free to correct any ...
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Multivariate Regression with Two Different Types of Response

Problem Setting: I have an interesting question related with longitudinal study and multivariate regression. I found that in lots of biomedical studies, multiple discrete and continuous endpoints are ...
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Confusion Surrounding "Marginal Models"

I was reading the following paper (https://www.stat.cmu.edu/~jiashun/Research/Area/Marginal.pdf) where Marginal Regression Models have been defined as follows: However, I was always under the ...
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Do Marginal Models by nature not have enough degrees of freedom (and therefore cannot fit)?

In the following text from Agresti's Foundations of Linear and Generalized Linear Models, I just don't get how equation 9.2 makes any sense. We are making a separate linear relationship between each ...
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Marginal model of longitudinal data with missing data

I have longitudinal dataset with measurements taken over years. I plan on modelling a marginal model with a binary outcome (0/1). My plan was using a GEE for this. This binary outcome has quite a ...
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When to choose mixed effect model over marginal model?

I am reading Applied Longitudinal Data Analysis by Fitzmaurice. However, I am confused as when to use mixed effect model. The book says in general when we want to study impact on individuals of the ...
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emmeans: command emmeans() or contrast(), whats the difference?

I fitted a glmer with a Poisson distribution and log link, including main effects and several interactions, an offset variable and a random effect. Something like this: ...
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Adding baseline covariates in stabilized weights change covariate balancing

I am computing weights using inverse probability of treatment weighting for marginal structural models (Robins et al. 2000). With both time-varying and time-invariant (baseline) covariates, some ...
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how to interpret the marginal effect on y from an etregess model of ln(y)

Using stata (with weighted survey design) I ran the following, where logwage is the log of wage. The log was taken because wage was not normally distributed. There is also information about the ...
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Interpreting log linear margins with endogenous treatment effects

I'm having trouble in understanding the predictive margins after a log linear regression with endogenous treatment effects. Using stata (with weighted survey design) I ran the following, where logwage ...
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Inverse probability of treatment weights and linear mixed effects models

I am encountering a problem when using inverse probability of treatment weights with linear mixed-effects models for a difference-in-differences analysis. I have longitudinal data on participants. I ...
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Interpretation of average marginal effects for categorical and continuous variables

I'd like to make sure I'm interpreting average marginal effects for categorical and continuous variables correctly (interpretation of binary variables seems straightforward). Using Stata, I ran a ...
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how to replicate the stata "margins, atmeans" command in R with the margins library [closed]

i'm trying to replicate the output of margins female, atmeans in R shown here: https://stats.idre.ucla.edu/stata/dae/using-margins-for-predicted-probabilities/ i ...
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GEEs cannot analyze demographic variables but GLMMs can?

I thought I was coming to understand the difference between (binary) GLMMs and Marginal Models using GEE...until I encountered the following passage in Hosmer et al (2013: 328): The clear weakness ...
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How to estimate the margins distribution using ecdf?

Suppose we have a random variables x. x <- rnorm(500, 2,3) Suppose that we do not know the marginal distribution of (...
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Is there a concept of closure under marginalisation for space-time models

Consider a diagonal VAR(p) model for data at S spatial locations and T time points. The marginal model for the data at a subset of spatial locations is a lower dimensional diagonal VAR(p) model. So in ...
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How to control for repeated measurements without controlling for between-cluster variability?

I want to explore the effect of the average prenatal maternal stress (cortisol level, continuous measure) on offspring growth during a linear growth period (monthly body size measure, N = 17 infants, ...
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Trying to calculate industry averages for female employees

I have a dataset that lists employers in a particular industry, the number of employees they have and the breakdown of employees as male or female. I'm trying to get a number that reveals something ...
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Getting a 0 correlation for Poisson marginal model in geepack in R

I'm trying to replicate Table 13.8 from Fitzmaurice, Laird, & Ware (2011) using R for teaching purposes. This is a GEE count model of the number of bacteria on 30 patients at two waves. In their ...
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The difference between average and marginal treatment effect

I have been reading some papers, and I am unclear about the specific definitions of Average Treatment Effect (ATE), and Marginal Treatment Effect (MTE). Are they the same? According to Austin... A ...
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MIXED MODEL - can a fixed factor be continuous?

I am using the linear mixed function in SPSS and want to determine whether a continuous variable (attendance) has an effect on the repeated measurement of my DV (<...
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Does this analysis make sense and can references to similar work be provided? [duplicate]

I posted this question previously here, but did not receive any answers. I'm resurrecting this question in hopes that someone might be able to provide some feedback and/or references. Hopefully this ...
StatsStudent's user avatar
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GEE Logistic Model with Subject Specific Predictions?

I have fit a marginal logistic model or GEE Logistic Regression model using SAS' proc genmod to obtain estimated parameters associated with mortality (death). Using SAS, I am able to obtain subject-...
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Marginal model versus random-effects model – how to choose between them? An advice for a layman

In searching for any info about marginal model and random-effects model, and how to choose between them, I have found some info but it was more-or-less mathematical abstract explanation (like for ...
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1 answer
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Subject specific vs population average predictions

I am in doubt whether in my thesis I should report on the subject specific predictions of the probability to respond with an 'I don't know' answer, or the population average. Consider for example the ...
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Difference between marginal and conditional models

A marginal model accounts for the correlation within each cluster. A conditional model also takes into account the correlation within each cluster. My questions are: Does a marginal model models ...
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