Prof. Joseph Hilbe (Univ. of Hawaii, Arizona State University, software
editor of “The American Statistician” and co-author, with James Hardin, of
the texts “Generalized Linear Models and Extensions,” and “Generalized
Estimating Equations”) will be giving his online courses on GLM and GEE
again at www.statistics.com. Statistics.com courses run 4+ weeks, require
about 10 hours a week and offer interaction with the instructor via a
private discussion board, reading assignments and exercises. There are no
set hours when you must be available.
GENERALIZED LINEAR MODELS (Aug. 27 – Sept. 24): Generalized Linear Models
extends ordinary least squares (OLS) regression to incorporate responses
other than normal. This course will explain the theory of generalized
linear models (GLM), outline the algorithms used for GLM estimation, and
explain how to determine which algorithm to use for a given data
analysis. For continuous response variables, the log normal, gamma,
log-gamma (survival analysis), and inverse Gaussian cases are
covered. Binomial (logit, probit, and others) as well as count models
(poisson, negative binomial, geometric) are also covered.
Register at:
http://www.statistics.com/content/courses/glm/index.html
GENERALIZED ESTIMATING EQUATIONS (October 29 – Nov. 26) provides
Generalized Linear Models (GLM) with the necessary extensions for panel
data (a group of subjects tracked over time). While relatively new, GEE has
become a standard technique for modeling panel data. This course covers
model construction, how to estimate the equations, different types of
models, how to deal with missing data, testing of models, model
assumptions, and more. Prerequisite: familiarity with GLM (Generalized
Linear Models).
Register at:
http://www.statistics.com/content/courses/gee/index.html
NOTE: You may also be interested in Prof. Hilbe’s course “Logistic
Regression” at statistics.com – it starts October 15.
Peter Bruce
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