Contents
Which is the best correlation structure for Gee?
You can use variograms and lorellograms to visualize correlation in longitudinal and panel studies. Intracluster correlation is a good measurement of the extent of correlation within clusters. Correlation structure in GEE, unlike mixed models, does not affect the marginal parameter estimates (which you are estimating with GEE).
Is the link function in Gee independent of the marginal model?
This is independent of any link function. The link function in the GEE is for the marginal model. Sites can be sources of unmeasured variation, such as teeth within a mouth, or students within a school district.
Which is the best correlation matrix to use?
One con- venient choice is the independence model, i.e., the identity matrix serves as the correlation matrix. It has been shown that in many cases the GEE estimates un- der the independence model (or some other structure) maintain a high efficiency (Zeger (1988), McDonald (1993)). There are exceptions.
How to choose the best independent correlation structure?
For an independent correlation structure you are essentially running the poisson model with robust SEs. So the estimates will be the exact same. The SE are usually larger. But sometimes robust SE are smaller (that is life: google with provide pain free explanation if interested) (4) See (1) and (2) above. (5) No.
When does an AR-1 correlation structure make sense?
However, when those assumptions are met, you get more efficient inference with the exchangeable. I have never found an instance when AR-1 correlation structures make sense, since it’s uncommon to have measurements that are balanced in time (I work with human subjects data).
Is there a QIC statistic for a Gee model?
GEE is not a likelihood-based method, so statistics like AIC, which are commonly used to compare models, are not available. However, the QIC statistic is available for GEE models and is analogous to AIC. Beginning in SAS ® 9.2, the QIC and QICu statistics are provided by PROC GENMOD for GEE models.
How does correlation structure affect standard error estimates?
Intracluster correlation is a good measurement of the extent of correlation within clusters. Correlation structure in GEE, unlike mixed models, does not affect the marginal parameter estimates (which you are estimating with GEE). It does affect the standard error estimates though. This is independent of any link function.
What do you need to know about Gees?
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 “working correlation” that I would like someone more knowledgable to clarify:
Which is an example of the Gee method?
The examples are simple enough to see the behind-the-scenes calculations and the essential role of weighted observations, and they allow nonstatisticians to imagine the calculations involved when the GEE method is applied to more complex multivariate data. Abbreviation: GEE, generalized estimating equations.
Which is better to use exch or Gee?
Choose exchangeable. My unambiguous answer is based on the most widely touted benefit of GEE: resilience of estimates to assumptions made. If you look at studies in your field you should see that exch is the default option. It doesn’t mean it is the best, but should be the first to consider.