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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GEE in SPSS: the case of ever-decreasing QICc values

I've been using GEEs in SPSS 22 to analyze my dissertation data and have discovered an interesting problem: when trying to figure out which subset of model factors have the lowest QICc, and therefore ...
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16 views

geepack: parameter estimates change sign depending on correlation structure

I'm working on a dataset with the following variables: ...
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17 views

GEE Repeated Measurements: Specifying Measurement ID

Say I have 10 subjects, coming from three groups. In each subject I make two measurements (one on the left, one on the right). ...
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44 views

How to analyze this messy design?

I need to analyze a data-set, with a very messy design, I am not sure how. I will try to make it simple. A new kind of stitches was invented, and is tested vs. 2 old kind of stitches. I will call ...
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1answer
23 views

Cluster size in generalized estimation equation (GEE)

I'm using the gee() function from the gee package in R. The problem I'm having is that the 'Maximum cluster size' that I get ...
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11 views

How to do and interpret a generalized estimating equation

My study is looking at the effects of enclosure type (1 IV (penned v not penned)) on the stereotypical behaviours and interactions (2 DV's (counts)) of elephants, however using rain (yes/no) and high ...
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2answers
47 views

Multinomial logistic regression with geepack in R

I am working on fitting a GEE model to a multinomial logistic outcome using the R package geepack. My understanding is that the package uses ...
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10 views

Can use an interaction between time and Time-varying-covariate in mixed model or GEE?

I have a data like this: Subjects Y Day X ID1 30 0 0 ID1 40 1 0 ID1 60 2 1 ID1 70 3 0 ID2 20 0 0 ID2 40 1 1 ID2 50 ...
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1answer
77 views

How can I estimate model predicted means (a.k.a. marginal means, lsmeans, or EM means) from a GEE model fitted in R?

I am trying to obtain model-predicted means and CI's for a categorical predictor in a GEE model fitted with the geeglm function (geepack package). The model is fitted with no problem, but where I am ...
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11 views

Naive vs. robust variance in GEE

I'm analyzing a data set including 40 participants. Each participant played a decision-making game 80 times. I am using a GEE analysis clustered by participant, with an exchangeable working matrix. ...
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31 views

fitting an exponential decay onto a regression line

I have data for adherence to medicines which follows a downward linear trend for about 6 months (from 100%) and then plateaus at about 50%. Another way of describing it is by saying that adherence ...
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1answer
151 views

Statistical Power of ROC/AUC Test with non-IID Samples :: To how many IID Samples are my non-IID Samples Equivalent?

I've been assigned to solve the following problem as part of a serious, biological research project. I think I have a tentative solution, but I'm wondering whether the approach I've picked is the ...
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1answer
29 views

What are the Mild Regularity Conditions in the context of GEEs?

I was reading the Wikipedia Article on Generalized Estimating Equations, where I came across the following sentence: Parameter estimates from the GEE are consistent even when the covariance ...
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57 views

Is this longitudinal data too complicated for GLMM or GEE?

After writing this post, I've realized that I am running around in circles, chasing my tail. Any help approaching this problem would be greatly appreciated, as I think I just need to bounce ideas ...
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28 views

Repeated measures design with measurements from different groups of animals

In a repeated measured design we measure a particular variable at different time points from the same subjects. In animal experiments, if animals are sacrificed at every time point to measure a ...
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67 views

Missing at Random Data in GEE

For a continuous outcome being analyzed using GEE with a linear link, you have assurance that standard errors and point estimates are consistent with a first order trend regardless of distribution of ...
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27 views

Interpret scale parameter from GEEGLM output in R

In GEE, the variance of each outcome is equal to the variance function multiplied by the scale parameter. For a continuous outcome the variance function =1. I understand that the scale parameter for ...
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1answer
74 views

Random or fixed effects in a GLM, or perhaps GEE?

I am involved in the analysis of the effect of an intervention at five different hospitals. The intervention aimed to increase the use of a particular equipement when treeating a patient, so the ...
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1answer
58 views

Weird looking binned residual plot

My binned residual plot is quite strange looking, the 95% confidence lines are so very jagged, with points between. I have colored this "inside" of the 95% confidence interval because it is really ...
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36 views

Marginalized local odds ratios structure in GEE

The ordLORgee command from the multgee package in R has an argument LORstr. With this argument the user can specify the ...
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34 views

GEE Combined with Linear Mixed Model

Suppose we have a linear mixed model with outcome variable $Y_{ij}$ and covariate $X_{ij}$. In particular, suppose we have a random intercept model: $$\mathbb{E}[Y_{ij}|b_i, X_{ij}] = \beta_0+b_i+ ...
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38 views

Combining Regression Equations

Suppose we are interested in English scores ($E_{ij}$) and Math scores ($M_{ij}$) in students in various classes. The scores are in different scales from each other. We perform two linear regressions. ...
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24 views

Number of cluster samples in GEE

In GEE, if you increase the number of clusters would this increase or decrease the standard errors of the regression coefficients? Would the estimated std error of the regression coefficients be ...
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1answer
77 views

SPSS outcome interpretation

I am very new with statistical programms, statistical analysis and SPSS. Now I even have to use the GEE function which seems to be a little too much for me. Do you ...
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1answer
46 views

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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28 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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16 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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71 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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37 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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37 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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25 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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493 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 – 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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96 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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44 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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2answers
88 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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250 views

Marginal model versus random-effects model – 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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197 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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248 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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1k 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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1answer
93 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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52 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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58 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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77 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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2answers
122 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
318 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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118 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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1answer
152 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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1answer
112 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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1answer
90 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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2answers
3k views

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 ...