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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12 views

Is it beneficial/feasible to use kenward-roger/satterthwaite degrees of freedom in generalized estimating equations?

Is it beneficial/possible regarding inferences to use kenward-roger standard errors in generalized estimating equations? I know kenward-roger is used with mixed-effects model when we have n<<p ...
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Alternative to Proc IML? Using SAS Viya without IML available [closed]

I'm running the SAS Viya environment and do not have access to IML. However, I need to use the following code, or something similar, to calculate standard errors accurately by combining the covariance ...
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4 views

Meaning of sigma2 parameter in longpower package in R

I'm trying to perform a power calculation for a longitudinal study - 2 groups and 2 measurement time points that will be analyzed using GEE. I've been trying to run the 'longpower' package. However, I'...
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ANCOVA or Repeated measures ANOVA or GLMM or GEE

I've got the following problem: background A unwanted species keeps entering the farms. Some farms might be entered more often than others. There are 80 farms in total, subdivided into two groups: ...
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28 views

survival package cluster and longitudinal data

I have longitudinal data on a recurrent event thus I tried the GEE method with the option cluster(id) in the survival package. I was wondering if I can keep my model even if there is no significance ...
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128 views

Why GEE estimates are smaller than GLMM?

Both are estimators that maximize the marginal likelihood, only GLMM does so by first considering the conditional probability, while GEE assumes a covariance structure of the marginal probability ...
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14 views

GEE or fixed effect regression with clustered SE

What should be considered when choosing between GEE for repeated measure (panel) data, and generalised linear models with clustered (on individuals) sandwich variance estimator? For example, change in ...
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GEEGLM or NEGBIN with offset person time follow-up

I am analyzing number of hospitalizations in 5 years of followup for a cohort of subjects. Some of these withdraw before the end of study. How can I consider it in a model for count data? Is it ...
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SPSS GEE: which type of model to select?

I would like to conduct a GEE analysis (repeated measures logistic regression) but I am not sure whether my data allows me to run a GEE Binary Logistic Model or if I should use GEE Binomial Identity ...
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Is there a model that can handled unbalanced repeated measures data with 1 OR 2 follow ups?

I want to identify predictors of a binary healthcare outcome in a purely observational study, and some of my participants have 1 recorded outcome timepoint, while others have 2 recorded outcome ...
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25 views

What is a sufficient sample size for a logisitic multilevel (three-level) analysis?

I have an exploratory research question for which I use a repeated measure design with 3 levels: level 1 = 3 measurement occasions per day level 2 = day level 3 = participan To keep the effort for ...
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27 views

GEE standard errors lower than standard errors assuming independence

I have a categorical dataset where the outcome is nominal (with three categories). There are 300 observations, and each individual contributes two observations to the dataset. When I analyzed the data ...
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Modeling repeated cross sectional clustered data

I have repeated cross sectional data from convenience samples of students nested in schools nested in districts. I have data on student-level behavioral outcomes (binary) and school-level program ...
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28 views

Modeling binomial outcomes with repeated measures

I'm looking at patterns of a particular injury within individuals and how they vary by age and sex. For each of 1365 individuals I have four locations each of which may be positive for this injury. ...
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Difference between Linear Mixed Regression and Generalized Estimating Equation Results

I am using commonly available iris dataset and trying to do following regression: PW ~ PL + SL + SW Since samples are taken from 3 "Species", this is kept as random or group variable. The ...
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Why not always use generalized estimating equations (GEE) instead of linear mixed models?

I read about generalized estimating equations (GEE) here, here and at other sites. It is mentioned in first of above links that "the parameter estimates are nearly identical" for linear ...
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Alternative to Mixed ANOVA without homogeneity of variances

As is tradition on these posts, I should say I'm relatively new to statistical analysis at this level so if I don't provide enough info off the bat bear with me. So I've conducted an experiment ...
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Analysing change in preference (proportion time, 3 repetitions)

I thought I'd ask for help here as I'm getting myself confused! In a nutshell, I am looking at the proportion of time animals spend in 4 sound conditions (each animal is tested 3 times) as a measure ...
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27 views

May Pattern-Mixture Models be used in conjunction with generalized estimating equations in addition to with mixed-models?

May Pattern-Mixture Models be used with generalized estimating equations for longitudinal data analysis? Hedeker et al mentions pattern-mixture models for handling non-ignorable drop-out patterns and ...
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May the fisher-scoring algorithm be used when we can only compute the quasi-likelihood?

May the fisher-scoring algorithm be used when we can only compute the quasi-likelihood and can't find the full-likelihood function? IE, some cases where it's advantageous to use GEE rather than Mixed-...
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27 views

Confusion about marginal vs conditional models and reversal of association

I've been reading Walter Stroup's Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2013), wherein the difference between "marginal" vs "conditional" models and inference is ...
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77 views

Post hoc test after GEE with repeated measures using R

I'm working on repeated measures design GEE and would like to get the result of post-Hoc test, but I don`t know how to do it. I just used those methods to get the result of post-Hoc test, but it ...
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95 views

How to deal with skewed distribution in GEE or GLM?

I have a group of repeated measurement data, the dependent variable (y) was skewed distribution when I build the GEE, should I transform y to a normal distribution variable first? Or Can I build the ...
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Are generalized estimating equations appropriate to use in this situation?

I’m an undergraduate doing research under a grad student. I’m trying to see if we’ve used generalized estimating equations correctly and if it’s appropriate for what we’re trying to figure out. ...
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GEEs for temporal autocorrelation and the ACF plot

I have a dataset with temporal autocorrelation in it. The response variables consists of 0s and 1s, and I used a binomial GLM first. However, when I used: residualsmodel <- resid(model) acf(...
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Panel Data Regression

Here (attached image), FTAs is my "Response Variable" and all the columns in the right are my "Covariates". It is clearly dependent on time so, there's a strong correlation. I want to find the most ...
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Comparing highly correlated predictors in log-binomial regression

I'm trying to figure out the best way to assess which of my highly correlated independent variables best predicts my dependent variable (y), a binary variable coded ...
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GEEGLM binomial modelling with Probit or logit

I am fitting a GEE model in R (multivariate binomial) There are no repeated measures and assume there is a within cluster correlation. If I use a probit link, do I have to exponentiate the output ...
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55 views

In R, does passing the IPW weights to the geeglm function in the geepack manage the Missing At Random (MAR) scenario?

Dear R users good at statistical modelling, please help me with this question. I want to use GEE in my analysis. Unfortunately, I have missing observations. It seems it is at least MAR, as I cannot ...
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114 views

If paired t-test tests mean differences rather than difference in means, what does GEE or mixed models followed by ANOVA analyze?

Paired t-test takes differences between data in two groups, say, time points. A subject must have both information: "pre" and "post". Otherwise the difference cannot be computed. So, the mean change ...
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GEE Std. Error Estimators: Pros and Cons of using jack-knife or bootstrap estimator of std. errors rather than sandwich when clusters$>30$?

What are the Advantages and disadvantages of using jack-knife, bootstrap estimator rather than sandwich (Huber-White) estimator in the context of generalized estimating equations? I heard sandwich ...
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65 views

GEE: results significant only with independent and exchangeable correlation structure

I am trying to fit a GEE Poisson model on a panel dataset consisting of T=360 and N=304 for a total of >108,000 observations in Stata. My response variable measures a count of people imprisoned, and I ...
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26 views

Deriving asymptotic variance of generalized estimating equation estimator (GEE)

As well known to us, K.Y. Liang and S. Zeger proposed GEE for longitudinal data analysis in their famous paper[1]. At the appendix of the paper, authors show the proof of Theorem 2. I tried to ...
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What exactly does it mean “conditional to random effect”?

I understand, that in (generalized) mixed models, the calculated $\beta$s are not population ones, but rather "conditional to the random effect". Let's say, I have a model, where I assess a set of ...
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141 views

What does it mean exactly to have marginal (population-averaged) or subject-specific effects, say in mixed models vs. GEE?

I know that mixed-effect models produce subject-specific answers and the GEE produces marginal effect. But I don't get it very well still, I'm sorry for a silly question. Let me explain what exactly ...
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65 views

Is it possible to use location-scale family distributions for mixed effects modeling?

Is it possible to use location-scale family distributions for mixed modeling or generalized estimation equations? The only location-scale family package I know of is GAMLSS in R which is for additive ...
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Is it valid to use a difference score between sequential timepoints as an independent variable in a longitudinal regression analysis?

Is it valid to use change scores, i.e. like change in body weight taken between consecutive time points in longitudinal analysis where I'm using nlme/gee? For example, bodyweight at hour 3 minus ...
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28 views

How to compute the prediction interval with poisson GEE?

How do I compute using R the prediction interval for poisson GEE via geeglm? I prefer geeglm because of the "waves" argument. Aside: I'm trying to predict what future counts of an event will be in ...
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Is it possible to do cross-validation with GEE?

Is it possible to do cross-validation with GEE and recursive partitioning trees? I wanted to use recursive partitioning on longitudinal data and them run the data through gee.
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158 views

May “offsets” be used in mixed-effects poisson regression?

Mixed-effects poisson regression studies counts for example of the incidence of a disease given the individual's random-intercept/slope. Mixed-effects regression studies individuals rather than ...
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Does poisson GEE require “scale.fix=TRUE” and “scale.value=1”?

Does poisson gee require scale.fix=TRUE and scale.value=1 for the package geepack? Aside: I heard gee package in r doesn't allow one to specify the scale.value and only let's one specify scale.fix=T/...
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78 views

Model validation with GEE-GLM

I am trying to find some resources on model validation for GEE-GLMs. Unfortunately I can't afford to purchase expensive textbooks and many of the books address GEEs using other software such as Stata. ...
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GEEs and GLMs: what can I do about the auto-correlation?

I want to run a model that somehow incorporates temporal autocorrelation. I have a dataset which consists of the minutes of Species A vocalizing at a single site. This is data recorded continuously ...
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67 views

Interpretation of mixed-effects versus GEE poisson/logit regression parameters

What's the difference in the interpretation of the model parameters (intercept +slope) in the mixed-effects model and GEE model for poisson and logistic regression?
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69 views

What do the different correlation structures mean with GEE?

What are the differences between the common options for correlation structures are and when do we use them, e.g. "independent", "exchangeable", "autoregressive", "unstructured", "fixed", "stationary", ...
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193 views

Is this possible to fit a MMRM (SAS REPEATED) with compound symmetry or AR1 model with glmmTMB?

MMRM (Mixed effect Model Repeat Measurement) models are special cases of the mixed models, where no random effects are used, only the residual covariance is modelled. This is commonly used for ...
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Multilevel versus clusteredness in the sample

does anyone can explain to me the main differences between multilevel estimations and clustering correction? I think with HLM technique we can get estimation to the random parameters (the group level ...
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126 views

Inclusion of clustering within a Cox PH model

I am working with multi-center data and modelling time-to-event data. I have included a cluster term within my model to account for similarities between patients that were treated at the same center. ...
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119 views

Advantages of using Cox model versus logistic GEE?

What are the advantages of using Cox proportional hazards model versus logistic GEE? Can one generate Kaplan-Meier remainder estimator curves using logistic GEE?
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154 views

How can the clustered robust standard errors be smaller than the model based ones?

I ran a GEE model and I used it to check the difference between the empirical standard errors and the model-based one. For almost the variables, the empirical standard error was greater than the OLS ...

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