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 ...

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12 views

Should I use GEE, Multilevel or Cox regression?

I am interested in the relationship between the number of hours worked per week and the chances of getting an illness. My dataset consists of 47 subjects, the predictor variable hours worked per week ...
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6 views

Maximum cluster size in geepack?

I'm analyzing resource selection using generalized estimating equations in geepack with geeglm. It is a binomial dataset with used and available points. My problem is that the models are running for ...
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27 views

Cluster selection and formula in (longitudinal) GEE models

I have a question according the "formula interface" from GEE models, for instance when using the gee function from the R gee package. Let's say I have a measured ...
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20 views

Possible to estimate average treatment effect (ATE) using generalized estimating equations (GEE)

I know that the method of generalized estimating equations (GEE) returns "population-averaged" coefficients, but for nonlinear link functions is it possible to use GEE to estimate the average effect ...
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13 views

How do I compare a continuous response variable across three levels of an IV at multiple time points when the IV is not fixed?

I'm proposing a project for a longitudinal data analysis class (it's about repeated measures ANOVA, GEEs, etc), but I'm a little stuck in choosing the correct analysis for my data. I have 20 years of ...
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12 views

Are you able to determine a effect size for GEE analysis using a multinomial, cumulative logit (SAS)

I am working on my discussion in my dissertation using a GEE model, multinomial, cumulative logit in SAS and I know I was not able to get a psuedo R but wondered if other ways to get an effect size. ...
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38 views

GEE with Mundlak-Chamberlain specification

I've only seen the Mundlak-Chamberlain (aka Mundlak aka Chamberlain* aka "correlated random effects": henceforth MC) specification applied in the random effects (RE) context. But is there any reason ...
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20 views

AR-M correlation structure in GEE

I am trying to use the GEE package in R to fit a GEE model to some clinical trial data. The model fits fine using independent, or exchangeable correlation structures. I'm trying to use an AR-1 ...
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21 views

Repeated measures with binary data

I've deigned an experiment in which participants read 24 narratives and guess if they are written by men or women and rate their own confidence. I thus have 24 binary repeated measures. I have the ...
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19 views

logistic regression (unique dependent variable, two time-varying covariates and one unique covariate)

In a case-control study, my independent variable (Y) is a dichotomous variable (abandon versus complete). To explain that, I have three continuous variables: two are time-varying covariates (i.e. a ...
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13 views

Marginal vs. Conditional Model

I have a question regarding GEE vs. GLMM. I know the probabilistic difference (marginal vs. conditional). What I want to ask, is when should I use each one. More specifically, in clinical trials, is ...
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12 views

R-Side GLMM vs. GEE

I wanted to ask what is the difference between an R-Side mixed model (with a binary outcome) and a GEE ? People often call an R-Side GLMM a "GEE type" model, but it ain't a true GEE, since it has also ...
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14 views

Analysing time series of unequal lenght

Hej all, I am analysing the pattern of snow melt with 5 replicates, at each of which there exist two experimental sites: one control, and one fenced exclosure for herbivores. I would like to ...
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28 views

Modeling Correlated Binary Data

I have data which looks like this: Subject ID (unique identifier), Group (Treatment or Control), Eye (Left / Right), Outcome (Success / Failure). The data is coming from a trial testing a new ...
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18 views

Advantages and Disadvantages of GLMM and GEE

I am making a list of disadvantages of GEE and GLMM for a correlated binary outcome. So far I know that GEE requires a relatively large number of clusters, and that it produces profile curves that ...
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1answer
17 views

Which model to choose: GLMM or GEE?

I have data with a binary outcome (success/failure) and a binary explanatory variable (treatment/control). For each subject (this is a clinical study), I have two observations, coming from two eyes. ...
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23 views

Notion of independence & logistic regression for clustered data from negotiation experiment?

I am currently analyzing data from a negotiation experiment, where 200 participants negotiated with each other in pairs (=> 100 negotiations). Personality traits of both negotiators and their ...
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21 views

Convergence of GLMM vs GEE

I am tring to figure out an issue which bothers me for quite some time, maybe you can help me understanding it. I wrote a SAS program to simulate the power (power analysis) for an experiment, where I ...
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54 views

How to compare GEE models with Linear models in R

I got a dataset, and I fit the data by linear model first and get a fitted model. and then I introduced a random effect, the subject or id in R arguments. and get a fitted gee model, so how to compare ...
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13 views

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 ...
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14 views

Model Predictions on Existing Data with a Single Covariate Manipulated?

I have a (logistic) regression model that I have used to predict mortality in a set of hospitals given patient and hospital characteristics. I have a model now that seems to predict quite well. ...
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20 views

Binomial or Poisson structure in GEE

I have a dataset with two total number of trials and two number of successes for each individual in two different situations. In addition, I have two groups of individuals, e.g.: ...
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16 views

geeglm with incomplete time series data

I have a time series data set (response variable measured 32 times during the year on 10 different subjects). At the time of measuring the response, also 3 environmental variables were measured. I ...
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34 views

Does this analysis make sense and can anyone provide relevent references?

I have a GEE logistic regression model that I've built that predicts that probability of mortality given a rather extensive set of covariates. I wanted to write here as a sanity check of sorts to ...
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72 views

Bootstrap Confidence Bands/Simultaneous Confidence Intervals for GEE Logistic Model

I have a relatively complex logistic model I built using generalized estimating equations (GEE). The model is used to predict population mortality. I have gone about estimating the mortality in the ...
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11 views

Do I use GLM or GEE. Determine the relationship of a continuous covariate on a 2x2 (within Subjects) interaction?

I have a 2x2 within subjects design with a continuous covariate. This covariate significantly alters the 2x2's interaction. I need to Determine the slope of the covariate's influence on the ...
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9 views

simulate random correlated binary variate

I'm using a generalized estimating equation (GEE) model to fit binary data. Using the original model fit on my observed data, I would like to simulate response variable, but because there is no ...
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9 views

Number of parameters for a GEE

How can I determine the number of parameters I have for each of 2 Generalized Estimating Equations, as well as the log-quasi-likelihood for each equation, using R? I am using the geepack library, R ...
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37 views

Bayesian estimation of GEE models

I'm facing a problem where I want to model a GEE with a tweedie distribution but it's not implemented in any R package that I found. I know that GEEs and linear mixture models (LMM) are somehow ...
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24 views

Should I use GLMM or GEE for analyzing data from a repeated behavioral economic game experiment (e.g., iterated prisoner’s dilemma)?

I have data from a repeated behavioral economic game experiment in which dyads play the prisoner’s dilemma game for 60 rounds. In each round, each player in a dyad decides to either cooperate (1) or ...
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34 views

GLMMpql and GEE differences for univariate time series

I am hoping to compare a GLS, GLM, and GLM with autocorrelation for a non-normal data set using their RMSE values. I was originally intending to use a GLM-GEE, because I have seen them used in the ...
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62 views

Discrepancy between Wald test and score test in Type-3 analysis in PROC GENMOD

My logistic regression model has a binomial response and 3 categorical predictors, A, B and C. A is binary B is ternary C is ternary The observations are clustered under a factor R. There are ...
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73 views

Conditional logistic regression or GEE in PS matched study

My situation: In a cohort study, I'm trying to find the correlation between outcome & Tx (Arm A vs Arm B). However, baseline covariates are unbalance between different treatment groups. Hence, ...
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9 views

link fx and distribution in GEE model

I am working on my dissertation using a GEE approach. The reason is that my outcome is nonnormal, nonlinear, heteroscedastic, and clustered. Additionally, it is also truncated (a cutoff score) and ...
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23 views

Generalizes Estimating Equations (GEE): How many factors are too many? [closed]

how many factors (independent variables) are too many when running Generalized Estimating Equations (GEE)?
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28 views

Generalized Estimating Equations (GEE): full factorial or separate interactions?

I have a question regarding full-factorial design and separate interactions using Generalized Estimating Equations (GEE). My research is about spatial biases and choice between the left and right ...
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219 views

Conditional vs. Marginal models

I have data with an outcome of 0 or 1 (binary) representing success or failure. I also have two comparison groups (Treatment vs. Control). Each subject in the study contributed 2 observations (the ...
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1answer
84 views

Interpreting a longitudinal generalized estimating equations beta cofficients

I've been struggling with wrapping my head around the GEE beta coefficients and I don't think I fully get it. There are other questions on CrossValidated that ask about GEE in the binary context ...
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69 views

SPSS Generalized Estimating Equations (GEE) with 2 nested subject variables?

I have an intercept-only model with 1 dependent variable and 2 subject variables (participants and participant groups). Technically, the participants variable should be nested within the participant ...
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53 views

Model selection of GEE using QIC: plausible models

I'm using GEE (generalized estimating equations) for the first time and selecting between multiple GEE using difference in QIC. The models differ in their independent variables. Here's my questions: ...
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1answer
50 views

Best method to analyse longitudinal recurrent count data

I want to analyze count data, more specifically number of prescriptions over 10 years. My first idea was to use the GEE Poisson. However, after reading some papers about recurrent history analysis I ...
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20 views

Why does GEE produce the same parameter estimates as OLS?

The quasi-likelihood function optimized under GEE is: $S_k(\beta)=\sum_{i=1}^{K}\frac{\partial\mu_i}{\partial\beta_k}\nu_i^{-1}(y_i-\mu_i)=0,$ where $\mu_i=h(\textbf{x}_i,\beta)$ is the conditional ...
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1answer
239 views

Case-control Matched Clustering in Generalized Estimation Equation (GEE) (R:geeglm)

Question: I have matched case-control data and I would like to take advantage of that in my GEE analysis. In the standard approach to GEE analysis, we call each subject a cluster and fit ...
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1answer
35 views

Analyzing binomial distributed variables

I have the following situation. A subject comes to the clinic at day 1 and is evaluated using a 10 item checklist. The sum of those 10 items is the subjects score. A intervention is performed. The ...
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42 views

Repeated measurements, multiply assessed exposure with single outcome

We have data points from a prospective study in which participants were assessed 3 times during follow-up for an exposure of interest, and during a 4th follow-up they were assessed for an outcome of ...
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45 views

GEE model returns GLM results

I have simulated some longitudinal data with 100 subjects and 7 measurements per subject. My data has random intercept which will induce "exchangeable" correlation matrix. My goal is to fit two ...
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25 views

GEE with three measurement points

I have done some research about predicting the occurrence of a disease. I had 3 measurements during 6 month and conducted a GEE with the dichotomous dependent variable Disease (yes/no) and several ...
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1answer
76 views

Calculating AUC for a GEE

I have used the geeglm package to build a GEE that predicts animal activity (a binary response, active or not) from weather data (e.g., Temperature, a continuous variable). TEMPC <- ...
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146 views

AR(1) working correlation matrix with GEE

I'm attempting to fit a GEE model and I have a question about using the AR(1) working correlation matrix. I've read some conflicting information about this correlation matrix. In some books and ...
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13 views

General question about generating data, using GEE and testing the results

I am new to GEE and try to understand it by using it. Now I have troubles to understand how the "gee" package in R works. I start by explaining what I intended to generate and what my questions are. ...