“Advanced Logistic Regression” is an online course offered at Statistics.com. Statistics.com is the leading provider of online education in statistics, and offers over 100 courses in introductory and advanced statistics. Courses typically are taught by leading experts. Some course highlights - A. Taught by renowned International Faculty (Not self-paced learning) B. Instructor led and Peer learning C. Flexible and Convenient schedule D. Practical Application and Software skills For more details please contact info@c-elt.com. Website: www.india.statistics.com

1. Online course
Advanced Logistic Regression
Taught by Dr. Joseph Hilbe
(http://www.statistics.com/logistic2/)
After taking this course, participants will be able to specify, implement and interpret the
output of a variety of advanced logistic regression models. This course moves beyond
the topics covered in "Logistic Regression" and covers a number of situations that call
for logistic-based modeling, including a variety of ordered-categorical response (both
proportional and non-proportional) models, multinomial models, panel models with
fixed and random effects, GEE and quasi-least-squares models, multi-level models,
survey logistic models, discriminant logistic models, skewed and penalized logistic
regression, median unbiased estimation, Monte Carlo sampling, and exact logistic
regression.
Who Should Take This Course:
Researchers in medicine, other life sciences, business, social science, environmental
science, engineering and other fields who need to predict or model 1/0 or "yes-no"
binary type responses as well as models having categorical and proportional responses.
Those who deal with classifying data into risk groups as well as those who handle
longitudinal and clustered data will find the course valuable.
Course Program:
Course outline: The course is structured as follows
SESSION 1
 Overview of binary logistic regression
 Overview of binomial logistic regression
 Proportional odds models
SESSION 2
 Ordered non-proportional models
 Multinomial logistic regression
 Multinomial probit regression
 Alternative categorical response models
 Marginal effects and discrete change
SESSION 3
 Panel models
 GEE/Quasi-least squares models

2.  Fixed- and random-effects models
 Multi-level models
SESSION 4
 Survey models
 Exact logistic regression
 Penalized logistic regression
 Monte Carlo sampling methods
 Median unbiased estimation
Instructor:
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.
This course takes place over the internet at the Institute for 4 weeks. During each course
week, you participate at times of your own choosing - there are no set times when you
must be online. The course typically requires 15 hours per week. Course participants will
be given access to a private discussion board so that they will be able to ask questions
and exchange comments with instructor, Dr. Joseph Hilbe. The class discussions led by
the instructor, you can post questions, seek clarification, and interact with your fellow
students and the instructor.
For Indian participants statistics.com accepts registration for its courses at reduced
prices in Indian Rupees through us, the Center for eLearning and Training (C-eLT), Pune.
For India Registration and pricing, please visit us at www.india.statistics.com.
Email: info@c-elt.com
Call: +91 020 66009116
Websites:
www.india.statistics.com
www.c-elt.com