IID:
"Independent, identically-distributed" is the assumption behind basic
modeling methods. The real world is rarely so conveniently
arranged. Data within a school may be correlated (when compared to
observations from other schools in the study).
Likewise for patient treatment centers in multi-center clinical trials.
Learn how to deal with data like this in "Modeling Longitudinal and
Panel Data: GEE" with Dr. Joseph Hilbe and Dr. James Hardin, in their
online course at statistics.com. For more details please visit at http://www.statistics.com/longitudinal.
This course
covers the extension of Generalized Linear Models (GLM) to model varieties of
longitudinal and clustered data, called panel data. Specifically, the course
treats generalized estimating equations (GEE), a population averaging method
that models panel data in which the response is a member of the exponential
family of distributions; e.g., continuous, binary, grouped, and count. GEE is
one of several methods used to model panel data - the most noted alternative
being random effect models.
The course will discuss GEE theory, relevant correlation structures, and differences in both theory and application between population averaging GEE (PA-GEE) and random effects or subject specific panel models (SS-GEE).
Who can take this course:
Social scientists,
medical and psychological researchers who need to analyze and model
longitudinal or panel data.
Course Program:
Course outline: The course is structured as follows
SESSION 1
- Theory and history of GLM
- Development of methods to analyze panel data
- Software used for GEE and related models
SESSION 2
- Model Construction and Estimating Equations
for Panel data in general and PA-GEE specifically
- Parameterization of the working correlation
matrix
- Scale variance estimation
- Alternating logistic regression models
SESSION 3
- SS-GEE models (random effect)
- GEE2 models
- Generalized and cumulative logistic regression
- Problems with missing data
SESSION 4
- Residual analysis
- Goodness-of-fit
- Comparative testing of models
- MCAR assumption for PA-GEE models
Dr. Hilbe and Dr.
Hardin are the authors of "Generalized Estimating Equations" (Chapman
& Hall/CRC). Dr. Joseph Hilbe is Emeritus Professor at the University
of Hawaii and Solar System Ambassador with NASA's Jet Propulsion Laboratory at
California Institute of Technology. He is an elected Fellow of both the
American Statistical Association and Royal Statistical Society. Dr. James
Hardin is on the faculty at the University of S. Carolina, and also on the
board of the "Stata Journal."
You will be able to ask questions
and exchange comments with the instructors via a private discussion board
throughout the course. The courses take place online at
statistics.com in a series of 4 weekly lessons and assignments, and require
about 15 hours/week. Participate at your own convenience; there are no
set times when you must be online. You have the flexibility to work a bit every
day, if that is your preference, or concentrate your work in just a couple of
days.
For Indian participants
statistics.com accepts registration for its courses at special prices in Indian
Rupees through its partner, the Center for eLearning and Training (C-eLT),
Pune.
Call: 020 66009116
Websites:
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