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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7 views

ANOVA/Chi-square analog to GEE

If repeated measures anova is analogous to random-intercepts regression and regular anova is analogous to multiple linear regression because of the F-statistic. Is GEE logit or GEE poisson or ...
10 views

comparing coefficient in increamental models with changing sample sizes

I have a panel data with 50 features over the course of 40 years. I want to evaluate the success of musicians. These 50 features cover 4 aspects of individuals careers. To uncover the importance of ...
62 views

How is nlme package in R “non-linear”? [closed]

Why is the package nlme non-linear? Is it non-linear in the sense that gee is non-linear because of correlation structure/covariance pattern like exchangeable/AR1? So if we drew out correlated errors ...
61 views

To GEE or not to GEE

I am post doctoral fellow in neurosciences. I have a quite basic question that I failed to solve by myself. In a pretest experiment for an fMRI study, we have asked to 3 age groups (~30 ...
70 views

GEE logit / Poisson versus mixed effects Poisson / logit

There's a way to do Poisson or logit mixed effects and Poisson or logit GEE in R. What's the difference between GEE and the mixed effects models for Poisson / logistic regression? I heard its the ...
25 views

How to build a model in GEE using poisson?

I am going to look for the association of summer temperature with different health outcomes. I have to use Poisson regression using GEE. These are time-series data and all the predictor variables ...
19 views

How could I get Prediction Interval from GEE model? Or how could I constructed using formulas?

I'm currently using GEE with Gamma link to fit model. The goal is to predict response variable for new data, I tried "Predict" function in r, but I also need Prediction Interval. I appreciate all the ...
69 views

Why estimate using GEEs inspite of their disadvantages over using ML?

I know sometimes I want to know the population-level estimates, but the problem with GEEs is I can't calculate the likelihood, and therefore all models I make with it aren't comparable, and I don't ...
31 views

Seeking to understand using the Firth correction in Generalized Estimating Equations to deal with quasi-complete separation

In order to deal with complete separation in my data someone suggested that I run penalized GEE (PGEE) by adding a Firth-type penalty term in R. Although I have read many papers on the Firth ...
32 views

Correcting for bias in GEE models with small cluster size

In GEE, several methods have been proposed for correcting for bias when the cluster size is small to moderate (<40). Some have proposed alternative variance estimators, e.g. Morel, Bokossa, and ...
57 views

Are predicted probabilities different when using a logistic GEE model vs. a logistic random effects model?

Are predicted probabilities different when using a logistic GEE model vs. a logistic random intercepts model? Let's assume for both models you use the same fixed effects and the same variable to ...
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Measuring effects of IV (constant) on DV

I have an independent variable (a bias) that is technically a constant. I want to measure the effects of the IV on the DV. How do I do this? I'm using SPSS. Let's say, participants produced A or B ...
62 views

Appropriate model choice for analyzing a cluster based longitudinal randomized controlled trial

I am performing a randomized controlled trial (RCT) of an educational intervention to improve knowledge, belief and practice among healthcare workers in hospitals. One hospital is assigned to the ...
73 views

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 ...
32 views

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 ...
53 views

GEE in R working correlation estimate not positive definite

I'm trying to replicate the following code from SAS in R: ...
43 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 ...
78 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 ...
88 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 ...
66 views

Circular smooths within a GAM-GEE framework

I have a predictor variable which I fit in a GAM as a circular smooth term: ...
45 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 ...
121 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 ...
402 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 ...
77 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 ...
260 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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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 ...
41 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 (...
35 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 ...
43 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 ...
245 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 (...
464 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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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 ...
37 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 ...
89 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: ...
163 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 ...
106 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 ...
30 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' ...
62 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 ...
233 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. ...
156 views

Covariate selection for GEE (R)

Using geepack, I fit the model: ...
115 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 ...
402 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), ...
44 views

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 ...
243 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, ...
22 views

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 ...
172 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,...
18 views

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 ...
112 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 ...