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Questions tagged [generalized-estimating-equations]

Stands for Generalized Estimating Equations which is an approach to estimating regression coefficients. GEE can be used on clustered / longitudinal data and has the attractive property that it provides consistent estimators of regression coefficients and unbiased inference even when the association structure within a cluster is mis-specified.

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Clarification on a GEE model including time-varying covariates

I was wondering if GEE method can work with time varying covariates? I have a longitudinal study which include time dependent covariates and I am not sure wether I can still use GEE model or not Based ...
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Is the GEE model an appropriate approach for this study?

I have the following data structure (longitudinal data). Over a period of several months, multiple tests (such as a vocabulary exam, a game exam, and a math exam) are administered to assess brain ...
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How to derive GEE from GLM?

I am now reading the lecture note from: https://dept.stat.lsa.umich.edu/~kshedden/Courses/Regression_Notes/gee.pdf Why do we have $V_{i}^{-1}(y_{i}-\mu_{i})$? I cannot link the last equation on page ...
doraemon's user avatar
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Is it valid to use "withdrew from study" in a mixed model to help with dropout bias in longitudinal data?

Consider the hypothetical dataset where a number of study participants have no change over time in a particular outcome, but their probability to drop out of the study is related to the baseline value ...
Evan's user avatar
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reproduce an analysis of a simple crossover trial using GEE from a paper

I am trying to reproduce the results in Table 6 from this paper entitled "The analysis of binary and categorical data from crossover trials". https://journals.sagepub.com/doi/epdf/10.1177/...
Statisfun's user avatar
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Using GEE models without clustered data

I am studying a set of longitudinal data with an N-of-1 approach. This means studying each patient in the data separately. I know there is correlation in my response variable and I am looking to use ...
chris202's user avatar
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How to calculate an effect size and confidence interval after running a Generalised Estimating Equation?

I am doing a randomised controlled trial and I need to use a GEE model for my statistical analysis. I have two groups (intervention and control) and I collect injured subjects every month (during 7 ...
user23539831's user avatar
3 votes
1 answer
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Logistic regression with complete separation AND repeated measures

Consider a typical logistic regression on data with a binary response $Y$, and some predictor variables $X$'s. I understand that when the event is rare, or in the case of complete separation, one ...
Ronald Carlos's user avatar
4 votes
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Understanding the Limitations of GEE

Review of GEE: Generalized Estimating Equations (GEE) are used to estimate the parameters of a generalized linear model. The main advantage of GEE is that they essentially allow you to model a ...
Uk rain troll's user avatar
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Statistical Comparison of Continuous Outcomes Across Groups with Identical Observations

Cross Validated community, I am working with a dataset of restaurants that have been classified by both Michelin and Rafaelo rating systems. Specifically, Michelin has categorized restaurants into A, ...
insan's user avatar
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Does GEE (Generalized Estimating Equations) need normality of residuals for inference in case of "approx. Gaussian" response?

A quick question. My intention is to analyze some numerical data across several categories (treat this as ANOVA, if you wish, but I'm going to focus on simple effects) that are "just numeric"...
FatimaShannn23's user avatar
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Asymptotic Normality for GEE Parameters

In the famous Liang and Zeger 1986 paper on GEEs https://www.jstor.org/stable/2336267?seq=9, they sketch a proof using the standard m-estimator arguments: (unstated) regularity conditions + first-...
Winston's user avatar
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How do I estimate and plot model predicted marginal means from a GEE model fitted using the multgee package in R?

I am trying to obtain model-predicted means and CI's from a GEE model fitted with the ordLORgee function in the Multgee package in R. I was able to fit the model and estimate the predicted means over ...
Sharon's user avatar
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3 votes
1 answer
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What are mixed effects without random effects?

Please pardon my ignorance, what is a mixed effects model without random effects, without any random intercept or random slope? Is this similar to marginal GEE model?
Ahir Bhairav Orai's user avatar
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censored gee model

Does anyone know if it is possible to fit a left censored GEE model with autoregressive correlation structure ? I know censReg can handle left censored repeated ...
Ahir Bhairav Orai's user avatar
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Coefficient covariance matrix of inverse probability weighted regression

I am interested in computing an estimate $\hat\Sigma_\hat\beta$ of the asymptotic covariance matrix of the parameter estimates $\hat\beta$ in a regression of $Y$ on $\{X, Z\}$, weighted by weighs $\...
Noah's user avatar
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How to choose between mixed effect and GEE

my outcome variable is on patient discharge disposition, with three categories(1.home,2.nursing home 3. hospital) my independent variable is based on hospital characteristics, eg bed (1. <500; 2.&...
Fanny0000's user avatar
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1 answer
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How to analyse a non-inferiority trial using GEE in R?

I'm trying to analyse a non-inferiority trial in R. Since there are correlated observations and a population averaged interpretation seems fine, I want to use GEE. To illustrate my problem, I will use ...
Mathemagician777's user avatar
10 votes
3 answers
566 views

longitudinal data with unequal samples and end points

I've been asked to look at a dataset of repeated measures taken during exercise in participants under two conditions control and ...
Jem Arnold's user avatar
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Managing Daily Quotas with Complex Equation for Resource Allocation

I have a complex resource allocation problem where I need to manage specific quantities while adhering to a daily quota of 3000 tonnes. The allocation is based on various variables, and I'm looking ...
Abdelhak Chana's user avatar
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Having trouble with geeglm convergence

I am trying to implement propensity score weighting in a GEE model with geeglm. I am also using bootstrapping to estimate the standard errors. However, I am running into a strange convergence related ...
aphe's user avatar
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Variable Selection for GEE or other Longitudinal Methods When Dealing with Many Variables?

I see the question of model selection for GEE come up and answers seem to usually involve QIC/MLIC for non-nested models, or LRT for nested. That's all fine, but when I have 50 predictors it's a bit ...
purple-blade's user avatar
3 votes
1 answer
124 views

Where does GEE formula come from?

I am trying to understand where GEE formula comes from. Here is the formula: $$Q(\beta) = \sum_{i}^{n} { \frac{d\mu}{d\beta}\boldsymbol{\Sigma}^{-1}(y_i - \mu)}$$ I am just wondering how they came up ...
stats_noob's user avatar
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How to calculate R-squared for the unequal number of LST and CO samples?

I want to calculate R-squared from LST and CO data in GEE. However, after considering the revisit time and cloud masking, I get very few data for Landsat-8 with respect to CO data. For example I have ...
usergeo's user avatar
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How to predict the outcomes form GEE regression across period of time

The recent paper by Liu et al. 2023 (https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajh.26998) describes a single-arm study on crovalimab. In the maintenance phase (weeks 5 to 25) patients were ...
Piotr's user avatar
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GEE Using a Bernolli Model and Log link

Conceptually I am interested in a pretty simple question: Do screening rates (dichotomous outcome) differ between an intervention and control group. We have a number of clinics that patients are drawn ...
Jordank's user avatar
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Why do you always need to interact the covariates with the slope in mutlilevel models?

On a number of occassions, I have seen people remark that you should always interact your covariates with the with your slope when running multilevel models. That is, for example, you should not run ...
statslearner13's user avatar
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Logic behind the direction of coefficient in generalized estimating equation

I am not familiar with statistics and thus nor am I familiar with the methodological reasoning behind it so can someone please explain the reasoning behind the following results: I have an outcome (...
Debby's user avatar
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1 vote
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What's the best model GEE or lmer?

I have access to individual data from 3 different studies. The first one has measurements of the variable of interest at baseline and 5 days after the intervention. the second one has measurements at ...
Ahmed's user avatar
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155 views

How to transform GEE coefficients to Cohen's d (standardized mean difference) for meta-analysis

I am conducting a meta analysis and am looking into how to convert coefficients (with SEs) from a GEE linear estimation into a standardized mean difference, Cohen's d. Does anyone have any hints on ...
Janina Steinert's user avatar
2 votes
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77 views

Replicate GEE from SPSS in R - differences in output

I am trying to replicate the results from a GEE I have done with SPSS in R. The dataset I am using can be found here SPSS Script ...
Michelle Smit's user avatar
2 votes
1 answer
256 views

ROC-AUC in GEE models?

I am wondering if it is possible to make ROC-AUC curves for GEE models? I found few papers who did that and it wasn't clear for me. I thought it was impossible given how they are marginal models. ...
Youknowme's user avatar
1 vote
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30 views

Longitudinal data in ML vs GEE

I'm currently working with pregnant women data. Given that the same woman could have multiple pregnancies over the years, I tend to use GEE to obtain odd ratios of my variables of interest. Now say I ...
Youknowme's user avatar
1 vote
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206 views

Binary logistic regression vs generalized estimating equation (GEE) for time series

I have time series with 322 observations. My dataset contains financial data. My endogenous variable, "target" is a binary variable. My exogenous variables are two continuous variables: &...
Oskar Bieńko's user avatar
1 vote
0 answers
64 views

Subsequent analysis on estimated marginal means from GEE

I have a set of data measuring response variable (length) on the same individual over several time points in nine different treatments (pH). Due to the confounding effect of temperature and it's ...
Sanja_'s user avatar
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1 answer
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How to define interaction between 2 categorical covariates and Time and Intervention in a longitudinal model? (in R)

Dears, Let's assume, that I have a study like this: longitudinal, 3 time points, T1, T2, T3. Let's assume T1 is post-intervention. 2 interventions, A and B 2 categorical covariates: Cov1 (2 levels: ...
OkkayashiNaruto's user avatar
2 votes
1 answer
848 views

GEE interaction interpretation

I’m trying to understand the interpretation of interaction terms, specifically in the context of GEE models. I’m familiar with them in conditional models, and am comfortable with marginal effects in ...
Andrew_99's user avatar
6 votes
1 answer
379 views

Wildly different answers replicating a GEE model from SPSS

Describe the bug I'm attempting to replicate a GEE model in statsmodels from a published paper that used SPSS (https://pubmed.ncbi.nlm.nih.gov/33279717/). I am getting very different answers for what ...
John Sakon's user avatar
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0 answers
251 views

geeglm correlation matrix interpretation

I chose an exchangeable var-cov mmatrix for my geeglm ...
Ahir Bhairav Orai's user avatar
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90 views

exchangable variance covariance matrix

I was trying to learn how to estimate exchangable correlation matrix. I asked ChatGPT to give me an example so that I can learn the steps and ChatGPT gave me this example ...
Ahir Bhairav Orai's user avatar
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1 answer
53 views

Cox analysis with a variable exposition with two measures at different times

I measured blood glucose for a sample of 500 participants at baseline and one year after. My issue is death. I already did a Cox survival analysis for the first blood glucose with my 500 ...
lodp75's user avatar
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2 votes
1 answer
272 views

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 ...
Nikaraguien's user avatar
0 votes
1 answer
37 views

GEE results showing opposite of true marginal relationship with EXCH working correlation

I am working on a modelling issue with two main effect variables: time period and Setting, related to an outcome, with all 3 being binary. My PI wants to test for moderating effects, so we have an ...
H. Dampf's user avatar
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55 views

If we use the GLS estimation to handle paired data, why can't we use the Welch unpaired t-test as well?

Let's assume I have a paired data to analyse, for example from a longitudinal study. A typical approach in biosciences is to use marginal (rather than conditional mixed) model, namely the linear model ...
YoannakisTsiatis's user avatar
1 vote
0 answers
55 views

When to use GEE vs. GLMM

I'm trying to decide whether I should use GLMM or GEE for my analysis. My study is repeat cross-sectional using longitudinal data (with 3 timepoints). I have a binary outcome and both continuous and ...
Statsbeginner's user avatar
2 votes
1 answer
54 views

How to analyse longitudinal data with 2 to 4 observations per person and varying time between observations

I have clinical data from about 300 patients with repeated measures/observations of psychological distress over time. Psychological distress is measured as a continuous variable, but could be ...
stats_curious's user avatar
1 vote
1 answer
246 views

Should be the baseline included in MMRM? MMRM vs. cLDA

In the cLDA (constrained longitudinal analysis) analysis the baseline value is already taken as a response, so it doesn't have to be included on the right side of the model. But in MMRM ANCOVA (mixed-...
JeromeKavassaki's user avatar
1 vote
1 answer
246 views

Solving estimating equation using R [closed]

I am working with different types of data and comparing a variety of estimating equation approaches which share a multi-dimensional parameter $\beta$. Given a set of data $\boldsymbol{X}$, is there an ...
J McVittie's user avatar
2 votes
0 answers
110 views

separate models vs joint model

My goal is to estimate the association between children BMI and distance to the nearest fast food restaurants. The hypothesis is that children BMI increases with increasing proximity of fast food ...
Ahir Bhairav Orai's user avatar
1 vote
0 answers
51 views

Testing association in repeated measures with zero in contingency table

I have a small dataset of repeated measures data (each participant (id) has up to two samples taken) and would like to determine if there is an association between ...
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