Tuesday, 20 March 2012

Generalized Linear Models (GLM)

Technique-driven statistical analysis can be like the blind men sent by the king to examine an elephant.  The man who feels the leg says an elephant is like a pillar, the one who feels the tails says it is like a rope, the one who feels the tusk says it is like a pipe.  It is left to the king to integrate the accounts, which he does masterfully (this tale is told by the king).  Dr. Joe Hilbe and Dr. James Hardin help to ensure that your own statistical focus does not narrow too quickly with the help of online course "Generalized Linear Models (GLM)".  For more details please visit at http://www.statistics.com/glm.

"Generalized Linear Models GLM" (Hilbe and Hardin) 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.  GLM allows the modeling of responses, or dependent variables, that take the form of counts, proportions, dichotomies (1/0), positive continuous values, as well as values that follow the normal Gaussian distribution. 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 touched.

Joe Hilbe and James Hardin are the co-authors of "Generalized Linear Models and Extensions" (Stata Press) as well as "Generalized Estimating Equations" (CRC Press).  They have lectured widely in these areas, and have been instrumental in developing computer routines for these methods - routines that have been incorporated into popular statistical software programs.

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, and Adjunct Professor of Statistics at Arizona State University. Dr. Hilbe has authored over one hundred journal articles and is author of the COUNT package in R, located on the CRAN website. He was also the first editor of theStata Technical Bulletin (now Stata Journal) and from 1997-2009 was Software Reviews Editor forThe American Statistician. Dr. Hilbe is Editor-in-Chief of the Springer Series in Astrostatistics.

Dr. James Hardin is a Research Associate Professor at the University of South Carolina. Co-author (with Joseph Hilbe) of Generalized Estimating Equations, Dr. Hardin is on the editorial board of The Stata Journal and is the developer of the Stata GEE command, and with Dr Hilbe is developer of the GLM command.

Who Should Take This Course?
Analysts in any field who need to move beyond standard multiple linear regression models for modeling their data.

Course Program:

Course outline: The course is structured as follows


SESSION 1: General Overview of GLM

  • Derivation of GLM functions
  • GLM algorithms: OIM, EIM
  • Fit and residual statistics

SESSION 2: Continuous Response Models

  • Gaussian
  • Log-normal
  • Gamma
  • Log-gamma models for survival analysis
  • Inverse Gaussian

SESSION 3: Discrete Response Models

  • Binomial models: logit, probit, cloglog, loglog, others
  • Count models: Poisson, negative binomial, geometric

SESSION 4: Problems with Overdispersion

  • Overview of ordered and unordered logit and probit regression
  • Overview of panel models

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 (www.c-elt.com).

For India Registration and pricing, please visit us at www.india.statistics.com.

Call: 020 66009116


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