Refers to 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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Interpretation of GEE coefficients

Suppose blood pressure is a continuous outcome variable and you run a linear GEE with following predictors: age (years), weight (lbs), and smoking (yes/no). How would you interpret the coefficients ...
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8 views

GEE iteration process

What is a simple description of how the GEE algorithm works? How exactly does the GEE process come up with the final estimates of the parameters?
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13 views

Estimating Equations

Suppose we have three random variables $X_1,X_2$ and $X_3$. Let $\bar{X}_{1:1:1}$, $\bar{X}_{1:1}$ and $\bar{X}_{2:1:1}$ be estimators for $\mu$. Note that the notation $\bar{X}_{1:1:1}$ indicates ...
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10 views

Correlated Random Effects Probit vs. GEE Population-Averaged Probit

My question relates to recent work on correlated random effects probit models (see these slides from Wooldridge) and comparing them to GEE population averaged probit models: Is one approach better as ...
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20 views

How to apply GEE and how to use it for critical mass

sorry I am completly new to the forum and as well to using GEE and SPSS so I hope my question is not to confusing. My dependent variable is the firm performance and I have several controlling ...
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19 views

Estimating a single proportion from a marginal or conditional model

I had a single sample of a binary outcomes (success / failure), and I wanted to estimate the population proportion with a point estimate and a confidence interval. The problem was that some subjects ...
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18 views

Analysis of repeated measures and repeated covariate

I would like to analyze data from a cohort study investigating the association between perceived discrimination and mental health outcomes (e.g. psychological distress) in two times (T0 and T1). The ...
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106 views

What do the tests of model effects and parameter estimates really tell (when an interaction is defined)?

A couple of times in LMM or GEE (with SPSS, though I doubt that matters ā€“ and might occur in other analyses as well, but these are the ones with which I have seen it) I have seen something that seems ...
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35 views

Generalized estimating equations, correct use and interpretation (SPSS)

I am trying to predict a choice (which software will the participants use?) using the psychological measurements taken when the participants tried out the four possibilities. I have used linear mixed ...
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33 views

Intercept only logistic GEE model

I have repeated measures binomial data for several subjects across several experimental sessions. I am interested in testing whether or not across all experimental sessions the group proportion ...
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50 views

Clustered data WITHOUT multilevel / GEE model?

I have a data-set with around 700 observations from 12 centres. Although the clustering effect as tested in a random intercept model didn't seem significant, it seems more appropriate to use a ...
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138 views

Marginal model versus random-effects model ā€“ 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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123 views

How to plot an interaction term, using a model's coefficients, of three-factorial GEE model with full-order interactions (geepack package)?

Using function geeglm from package geepack (Generalized Estimating Equation), I have modeled counts as being dependent on two ...
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85 views

Residual analysis and diagnostics for GEE Models in R

Some colleagues asked me to perform a residual analysis on both linear models and generalized estimating equation (GEE) models. I know it is a faux-pas in some circles to remove outliers, but in our ...
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266 views

GEE: choosing proper working correlation structure

I am an epidemiologist trying to understand GEEs in order to properly analyze a cohort study (using Poisson regression with a log link, to estimate Relative Risk). I have a few questions about the ...
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67 views

Covariance pattern models versus generalized estimating equation models

Can somebody please explain the major differences between covariance pattern models (Hedeker and Gibbons, Chapter 6, 2006; Jennrich and Schluchter 1986) and generalized estimating equation models ...
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42 views

GEEs in case of a small number of clusters with strongly heterogeneous cluster size

My data set includes 400 records. Each record comprises values for the binary outcome variable $y$ and 12 categorical predictor variables $x_1, ..., x_{12}$, most of which are binary too. The records ...
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37 views

Lasso for GEE model

Can a LASSO be applied for predictor selection in a logistic GEE (generalized estimating equations) model for longitudinal data? Is there an implementation of LASSO for a logistic GEE model for ...
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53 views

Select the covariance structure or the model first for GEE?

I have data with repeated measurements and a binary outcome (Yes/No). I want to use GEE to model the data with a logit link function. Let $\pi=P(yes)$, then I want to consider the following five ...
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64 views

Specifying the correlation structure of an unevely spaced time series in GEE with geepack

I have counts of plants from different sites over a number of years. In each census year, all sites were surveyed, but the gaps between census years vary (between 1 and 4 years between consecutive ...
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1answer
146 views

How many clusters for linear mixed models and GEE?

I have a data set with repeated measurements on subjects. The total sample size is $n=118$ and the number of clusters (i.e. subjects) is $m=49$. The smallest cluster is of size 2 and the largest ...
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60 views

Dealing with nested factors and correlation structure in a GEE model

This question is of a previous one that has not been answered yet (see the details of our experiment and question here). We are now exploring a GEE (Generalized estimating equation) approach that ...
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107 views

Does the sandwich estimator in GEE protect against both correlation misspecification and heteroscedasticity?

The relative merits of GEE with exchangeable correlation or GEE with independence and the sandwich estimate have been discussed, but I couldn't find a post specifically addressing my question. I have ...
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98 views

Agreement of clustered data

I have the following situation: I have analyzed several data curves from a group of patients (16 curves per patient) with different analysis methods and want to test for the agreement of the methods. ...
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88 views

Why might it be important to specify a family when using GEE if it doesn't make any assumption about the joint distribution?

I understand that one of the advantages of GEE is that you make no assumptions about the joint probability distribution, relying instead on the mean, the variance and the associations (corr). Why then ...
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71 views

(Generalized estimating equation) Why does convergence status change when changing scales of variable

I'm working on a generalized estimating equations model. Originally there are continuous independent and dependent variables at individual levels, from which I also create dichotomous independent and ...
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How to conduct a multilevel (hierarchical) binary logistic regression (in SPSS, R, or other software)?

I have a model with occurrence of a disease represented by a binary dependent variable (DV) and 8 independent variables (IVs) at different levels. I need to create a multi-level model, in which the ...
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106 views

Missing data: generalized estimating equations and generalized linear mixed models

I have a repeated measures data set with 5 time points and one binary dependent variable (yes/no response to a question). There are around 20 subjects. If my understanding is correct, both ...
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282 views

How is the working correlation matrix estimated for GEE?

From a slides How does GEE work? First, a naive linear regression analysis is carried out, assuming the observations within subjects are independent. Then, residuals are calculated from ...
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95 views

Methods for cross-sectional twin data (GEE, mixed effects modeling, GLMM)?

I have a twin dataset of 248 pairs (166 MZ, 82 DZ) that was gathered at one time point. I'm interested in looking at the relationship between a physiological biomarker and self-reported insomnia ...
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49 views

Difference between quasi-likelihood estimating equations, IEE and GEE?

What is the difference between quasi-likelihood estimating equations, and GEE? From a note Quasi-score function is for independent, over-dispersed data (Poisson or binomial), while GEE1 is for ...
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87 views

How do I compute a prediction interval from generalized estimating equation output?

Suppose I have repeated observations on individuals, which I've analyzed using a generalized estimating equation (GEE). What is the procedure for computing the prediction interval for future ...
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51 views

User-defined contrast on Generalized Estimating Equations

I am running a GEE on SPSS as well as Stata on choice data with the following structure: Each subject completed 32 trials in 4 ...
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72 views

Generalized estimating equation and data format

I first summarize the analysis of some papers that I want to imitate. The regression looks like: ...
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131 views

Diagnostics for GEE in R

I have been checking out which diagnostics to use for a GEE analysis. It seem that influence measures are appropriate (Preisser, 1996). Does anyone know of a package that can be used in R to examine ...
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122 views

Within-subject correlation before deciding on correlation structure in GEE

I want to have a look at the correlation coefficient for repeated measures in $x$ number of individuals. This will help me chose which correlation structure will best fit in GEE (Generalized ...
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107 views

When can the variance be written as a function of expectation?

What kinds of distribution have variance as a function of expectation, i.e. let $X$ be a random variable of a distribution, $Var(X) = f(E(X))$ for some function $f$ ? Sufficient conditions including ...
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180 views

GEE, quasi-likelihood and what it generalizes

Wikipedia formulates Generalized Estimating Equations (GEE) as Given a mean model, $\mu_{ij}$, and variance structure, $V_{i}$, the estimating equation is formed via: $$ U(\beta) = ...
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152 views

Models for Generalized Estimating Equation?

From Wikipedia, Generalized Estimating Equation (GEE) is a method to estimate the parameters of a generalized linear model (with an exponential family distribution for the response). By reading other ...
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76 views

Suggestion for statistical analysis. Is generalized estimating equation (GEE) a good option?

I have two groups a G1 and control. For both groups we measured their cell counts every 10 minutes: 0 to 650 min. We are trying to find: Difference (in cell counts) between G1 and controls - ...
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91 views

GEE: Pairwise comparisons at different levels of a covariate?

I'm familiar with basic regression methods, but have no experience using GEEs. I use SPSS, and I'm trying to use a GEE for a dataset that I have, because there is a repeated measures component in my ...
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68 views

How can generalized estimating equation be applied to analyze network data?

I'm using the analytical strategy of Christakis and Fowler to study the spread of behaviors in social networks. Page 566 of this article reviews their method in more details: ...
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376 views

GEE (or GLMM) in SPSS: Interpreting outputs and model selection

I am attempting to analyze my (experimental psych) data in SPSS, and I have a few questions regarding the kind of analysis I should be using (GEE or GLMM), how I should be interpreting the output, and ...
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188 views

How to interpret Generalized Estimating Equation output?

I was wondering if anyone could help me with a query regarding Generalized Estimating Equations (GEE). Background: Iā€™m looking at the effect of treatment on the feeding rate (counts of casts) of a ...
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42 views

Help modeling school consent rate changes after an intervention

I have # of students consenting to be vaccinated and # of students eligible to be vaccinated for 77 schools in three school years (2010/11, 2011/12, and 2012/13). Between 2011/12 and 2012/13 there was ...
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Is it necessary to used clustered data analysis techniques on matched designs?

We have cancer outcomes from SEER data matched on registry and age where exposed and unexposed individuals were matched in a 3:1 ratio. There are still 1,000s of cases per registry in either group. ...
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62 views

How to analyze data with more than one associated categorical dependent variables?

I have some dependent variables related to the growth of a company having categories like (e.g. for variables indicating net profit, financial turnover etc.) (1) decreasing, (2) stable, (3) ...
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50 views

Regression with some associated ordinal dependent variables

I have some associated categorical dependent variables that are ordinal in nature (with 4 or 5 categories). If I want to see the effect of a set of independent variables (which can be both continuous ...
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69 views

Can GEE handle small unaccounted clusters in data?

A survey is being administered in a resource intensive setting. A 2-phase study design will be implemented using cases and controls identified by a certain behavior (say, smoking) and they will be ...
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97 views

How can I get annual rates of change for combined trend estimates?

I would like to combine trend indices (gained with different methods referring to the same subject, assuming they do not differ significantly) of two different time series and to derive the combined ...