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Questions tagged [gee]

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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How to model a sequence of binary choices: Generalized Estimating Equations (gee)?

For the sake of example, let’s say this is a costumer research study with a 3 by 3 factorial design, in which I am studying whether customers make purchases or not depending on various factors. I ...
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Sample size calculation and number of independent variables for repeated measures Generalized Estimating Equations

I'm trying to understand sample size estimates for repeated measures Generalized Estimating Equations. Reading papers on this topic, it seems that the number of independent variables are not assumed ...
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GEE in R working correlation estimate not positive definite

I'm trying to replicate the following code from SAS in R: ...
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17 views

Selecting a Correlation Structure for GEE

I am using Poisson regression with a log link, to estimate Relative Risk and need some guidance on selecting a correlation structure. My observations are courses of antidepressant treatment where a ...
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43 views

GEE vs GLMM in large sample size?

I am running two longitudinal models for two different populations I'd like to compare. N1=4,000 individuals (translated into about 20,000 rows; 18 variables) and N2=400,000 individuals (~4 million ...
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18 views

How to estimate the VIF for geeglm models in r

I am very new in r and at analyzing gee models. I have a very high dimensional data (51 independent variables measure at multiple times with no missing values (secondary dataset)). I am pretty sure ...
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32 views

Circular smooths within a GAM-GEE framework

I have a predictor variable which I fit in a GAM as a circular smooth term: ...
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35 views

Can I use a mixed model even when my independent variables are all fixed effects?

I need to use longitudinal data for my model. Two possible options to deal with the lack of independence between observations: GEE and Mixed models. But, how Mixed model can even be an option if all ...
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64 views

How to estimate model predicted means per group from a GEE model fitted in R?

This question is related to a similar post: How can I estimate model predicted means (a.k.a. marginal means, lsmeans, or EM means) from a GEE model fitted in R? The difference is that I do not only ...
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130 views

GEE vs mixed model for time-varying covariate

Assuming the attached dataset, I am looking to examine whether participants who are treated are more/less likely to have high addiction severity compared to non-treated. Both treatment and high ...
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61 views

Is this an obvious situation for Generalized Estimating Equations?

Imagine collecting data in two locations at three points in time. The same 500 or so people are interviewed repeatedly, a year apart, in each place. There are many things being asked but of interest ...
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123 views

Do GEE and GLM estimate the same coefficients?

In a GLM, the likelihood equations depend on the assumed distribution only through the mean and the variance. The likelihood equations are $$\sum_i^n (\frac{\partial \mu_i}{\partial \eta_i}) \frac{...
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68 views

Can I used a General Linear Mixed Model when there are repeated observations for only a small proportion of cases?

I am trying to make a model with a response variable of performance on a test (interval data), along with predictors for test performance. It's a threshold test, so anyone that passes it will not have ...
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34 views

Marginal interpretation of fixed effects in GLMM

I understand that when applying GLMMs (e.g. in logistic mixed effects regression), the interpretation of the coefficients for the fixed effects is that they are also conditional on the random effects (...
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31 views

Quasi-likelihood Estimation and Linear GEE

I am trying to better understand some of the assumptions of the estimator I am using, which is linear GEE. It is my understand that linear GEE uses quasi-likelihood estimation and so it has weaker ...
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24 views

Generalized Estimation Equations 3 levels

I have a dataset where students are nested within classes, and classes are nested within schools. I am interested in evaluating the effects of a treatment delivered at the student level. The response ...
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160 views

What is the main difference between GLM and GEE?

From my understanding, glm(not glmer) and GEE both handle binary values. But GEE is a marginal model and glmer is a random effects model (mixed model). So then what is the main difference between GLM (...
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243 views

GEE vs LME, non-normal distribution

I have a question about statistics theory. I have longitudinal, repeated measures data where the response variable is skewed right. Using R, I ran a linear mixed-effects model (good for longitudinal, ...
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39 views

How to bootstrap data with unknown correlation structure?

I am interested in how to validly bootstrap data with an unknown correlation structure. Let's say I am bootstrapping in order to obtain inference for some smooth function of the data similar to a ...
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28 views

Ordinal logistic GEE sample size estimation

I am looking for ways of doing power analysis for ordinal logistic GEE (currently in SPSS, but open to attempting R or something else). My understanding is that this will not be possible in software ...
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50 views

Significant interaction effect for a subgroup but not overall

I fit a GEE model looking at the relationship between cognitive score and head impacts. Head impacts is a categorical variable separated into 4 quartiles by amount of exposure. Here are the results: ...
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114 views

Why does ignoring dependencies between observations *inflate* my standard errors?

In the introductions to books and review papers about modeling dependent (a.k.a., within-subjects, repeated-measures, clustered, longitudinal, hierarchical) data, it is very common to say that ...
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72 views

Diagnostic methods for GEE models

Is there a way to assess the "goodness of fit" of a GEE model besides using some numeric criterion (e.g. QIC) ? I was thinking about residuals distribution analysis but I couldnt find any assumption ...
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23 views

GEE vs. fitting a simple model to each subject and then test the parameters across subjects

In my experiments, participants (N=50) are asked to play a decision-making game several times. I am interested in testing whether a certain factor "F" (present/absent) influences participants' ...
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52 views

Plotting interaction of categorical predictor and continuous modifier

I fit a GEE model examining the interaction between my predictor: heading quartile (categorical- dummy coded) and a moderator variable: head circumference (continuous). I would like to visualize the ...
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155 views

Issues fitting logistic GEE model in R [closed]

I am trying to predict the probability of having symptoms (binary) after unintentional impact (3 categories: 0, 1, 2+). However, I am having difficulty fitting the logistic GEE model in R. ...
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120 views

Covariate selection for GEE (R)

Using geepack, I fit the model: ...
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59 views

Repeated measures with ordinal response and two categorical independent variables

I am trying to test this difference in students results (ordinal response variable; 1 - above expected, 2 - working at expected, 3 - working just below, 4 - working below) for two periods of time in a ...
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296 views

How to simulate data for generalized estimating equations (GEE) with logistic link function?

I am working with a pre/post test structure, measuring dichotomous outcomes. I am using GEE to estimate the coefficient for time (also a binary variable, 0 representing pre and 1 representing post), ...
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73 views

Intuitive explanation of the Wald Chi-Squared Test

I am having trouble understanding what the Wald Chi Squared test is used for intuitively. SPSS uses the Wald Test (type III) in the "Tests of Model Effects" box when I run my GEE models, but I don't ...
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Perform GEE regression in R with multiple dependent variables

Im trying to perform generalized estimating equation (GEE) on the (sample) dataset below with R and I would like some little guidance. First of all I will describe my dataset. As you can see below it ...
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157 views

GEE and GLS. Are they similar?

First of all there is another question about it here, but it has no answers unfortunately...And also here, but it is more general about mixed models and GEE, while my question is more specific... So, ...
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Must individuals have more than one observation for repeated measures analyses?

In cohort studies of change over time (for instance change in repeatedly measured weight after a dietary intervention, using linear mixed models or GEE), what is the detriment of including individuals ...
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162 views

How to interpret GEE parameter estimate for Multinomial Ordinal Data

I have the following experimental design. There are four diet charts (A, B, and C, D). For each diet, a group of 25 subjects (1, 2, 3…25) was on each of those four diets. And they are supposed to ...
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105 views

multgee for repeated measure multinomial regression

I am trying to analize my experiment results according to the multgee reference pdf, but I have some warning message. My dependent variable is a 5 level categorical variable. I have 12 eyes of 6 rat,...
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How to do one-tailed test of proportion vs. known proportion with repeated measures (GEE, power analysis)

I may be over-complicating this, but I'm looking for advice. Effectively, the question can boil down to something like: "How likely is it that people answer less than 90% of the questions from a bank ...
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101 views

Propensity matching and analysis of resultant data on a data set with repeated measures

We have extracted retrospective case-level data collected over several years. We are using the administration of rescue antiemetic in the postanesthesia care unit as a proxy for postoperative nausea ...
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Numerical Algorithms for GEE versus GMM

Generalized Estimating Equations (GEE) are specified by k equations for k unknown parameters, while Generalized Method of Moments (GMM) are specified by p equations for k unknowns, with $p>=k$. ...
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399 views

Mixed Model Versus GEE estimates and which to use

I am new to both GEE and mixed modeling, so please bare with me: Briefly: my exposure is television viewing in childhood (tv) and I am trying to assess change in body mass index (bmisds) over 3 time (...
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Generalized Estimating Equation Correlation and Interpretation

I am extremely new to this, so bare with me: I am trying to run a generalized estimating equation analysis to assess the association between television viewing in childhood (coded categorically as "...
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83 views

Sensitivity Measures for GEE Model

Is there any method (e.g. like Cooks D) implemented in R to identify leverage points for GEE Models? I used geepack to fit my models and would like to do a sensitivity analysis now. However, I don't ...
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What is the difference between using a standard logistic regression model versus a marginal model?

I have been analyzing a longitudinal dataset and came across a peculiar finding. I have been using a marginal logistic regression GEE to analyze the regression coefficients, standard errors, Z-scores ...
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56 views

stacked data and binary logistic regression

I am conducting research where I investigate gap acceptance by pedestrians. One of the statistical tests which I would like to carry out is binary logistic regression or any similar test. I am asking ...
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57 views

including the same variable as a time-varying and time-invariant covariate in MLM

I am wondering if the same variable can be used as both Time-varying and time-invariant in the same GEE model. The data set includes: DV - a proportion of young employees in an organization Another ...
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496 views

Why Generalized estimating equation (GEE) is not popular?

I am a newbie in econometric analysis. When I was in Master and PhD course of public health field, I learned mainly about mixed model and GEE for panel data analysis. I learned GEE is robust, does ...
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225 views

Effective sample size reduction for correlated data analyses

In power and sample size calculations, and minimum detectable effect analyses for GEE, I have often seen an effective sample size reduction used to account for correlation. The idea is that the more ...
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154 views

GEE interpretation

I'm new to stats, but I'm working with an SPSS guy. I'm more of an R person. I got R to run the GEE my partner suggested we use without any errors, however my output looks completely different from ...
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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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294 views

Power Calculation for GEE

I have performed a rather tricky analysis of some longitudinal data and now wish to do a retrospective power calculation. I ran a generalised estimating equation analysis for data that consisted of ...
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35 views

GEE analysis using proc genmod block effect

I have done an experiment with two factors in RCBD, bionomail distribution. I wanna use GEE in Proc Genmod in SAS to analyze the data as follow: proc genmod data=Emerg; class obs Crop Dist Block; ...