Thursday 13 September 2012

Modeling Count Data


Do you work with binary, categorical, or count data?  You'd be a rare analyst if you didn't.  There are lots of details to consider - when to do exact tests, what they are, how to handle ordinal data, the role of modeling as opposed to significance testing, what to do when the assumptions required for Poisson regression fail, and much more.  Learn more in online course "Modeling Count Data" (Dr. Joseph Hilbe) at Statistics.com.

"Modeling Count Data," deals with regression models where the response or dependent variable is a count or rate. A count is understood as the number of times an event occurs; a rate as how many events occur within a specific area or time interval.The course will cover Poisson regression, the foundation for modeling counts, as well as extensions and modifications to the basic model. Extensions are required when the assumptions underlying the Poisson model are violated. Negative binomial regression is the foremost method used to extend the Poisson model. Since Poisson assumptions are rarely met in practice, substantial attention will be devoted to the negative binomial model and its variants. For more details please visit at http://www.statistics.com/count/.

Who Should Take This Course:
Analysts and researchers in a wide variety of fields who are concerned with modeling counts and rates.

Course Program:

Course outline: The course is structured as follows
SESSION 1: Overview of Count Models and Methods of Estimation
  • Varieties of count model
  • History of count models
  • Derivation of GLM-based algorithm
  • Derivation of maximum likelihood count models
  • Methods of assessing fit for count models
  • Residual analysis
  • The nature of risk and risk ratios

SESSION 2: Poisson Regression and the Problem of Overdispersion
  • Poisson regression
  • Creating synthetic models; simulation
  • Predicting counts
  • Effect plots
  • Marginal effects/Discrete change
  • Parameterization as a rate model
  • Defining extra-dispersion: varieties
  • Problem of overdispersion: apparent vs real
  • Tests for handling overdispersion
  • Negative  binomial extra-dispersion

SESSION 3: Negative Binomial Regression and Alternative Parameterizations
  • Negative Binomial Regression: varieties, derivation, and distributions
  • Synthetic data modeling
  • Marginal effects/Discrete change: NB models
  • Binomial vs Count models
  • Geometric regression: canonical and log
  • Alternative parameterizations: NB-1, NB-C, NB-H, NB-P
  • Generalized Poisson and negative binomial models
  • Extended Poisson models: bivariate; Poisson-inverse Gaussian; double Poisson
  • Extended negative binomial models: bivariate; others

SESSION 4: Problem with Zero Counts; Censored and Truncated Models, Latent Models
  • Zero-truncated models
  • Zero-inflated models
  • Zero-altered models
  • Hurdle models
  • Censored count models
  • Finite Mixture models
  • Quantile count models
  • Exact Poisson and negative binomial regression
  • Project preparation

Dr. Joseph Hilbe is President of the International Astrostatistics Association, an Emeritus Professor at the University of Hawaii, 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 some twelve books on statistics, over one hundred journal articles, and various packages and functions for Stata and R.  and is author of the COUNT package in R, located on the CRAN website. Dr. Hilbe is Editor-in-Chief of the Springer Series in Astrostatistics.

You will be able to ask questions and exchange comments with Dr. Joseph Hilbe 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.

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

Call: 020 66009116

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