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.
Call: 020 66009116
Websites:
No comments:
Post a Comment