Logistic Regression Models: Modeling Binary, Proportional and Categorical Response Models
Date: Location: Course duration: Software: Level: Delivered by: Course Code:	15-16 October 2012 Washington, D.C., USA 2-days Stata Intermediate Prof. Joseph M. Hilbe, Arizona Stata University ST-113-USA

Contents

Back to top

Course Overview

Timberlake Consultants invite you to attend the following two-day course to be held in Washington, D.C.,USA.

The course provides clear and understandable guidelines on logistic regression based modeling, including the modeling of binary, proportional and categorical response models. The course guides participants in how to select the most appropriate model for a given data situation, then how to best construct, interpret, and comparatively evaluate each type of model as to its fit. Discussed are the standard binary and grouped logistic models, and their extensions; eg proportional odds, partial proportional odds, multinomial logit and exact logistic models. Longitudinal and panel logistic models as well as Bayesian logistic models will also be discussed.

Back to top

Agenda

Day 1: Morning

1. Nature of risk, odds, and odds ratio
2. Methods of estimation: maximum likelihood; IRLS
3. Binary logistic regression: The logistic algorithm; Model construction, interpretation and model fit; Marginal effects; calculating probability
4. Grouped logistic regression; converting observation-based models to grouped; analysis of table data
5. Over dispersion: Identifying and methods of handling extra-dispersion; Tests for extra-dispersion
6. Relationship of count and binomial models

Day 1: Afternoon workshop

• Software considerations for modeling and evaluation of logistic models
• Setting up a logistic model: from tables; from grouped data; from observation data
• Exercises in modelling - selecting the appropriate model for specific types of data
• Constructing synthetic logistic models; testing model assumptions
• Constructing a logistic model project

Day 2: Morning

1. Overview of categorical response models
2. Proportional odds models
3. Partial proportional odds models
4. Multinomial logit models
5. Logistic longitudinal and panel models: fixed, random, and mixed effects models
6. Exact logistic regression models
7. Survey logistic models
8. Bayesian logistic models

Day 2: Afternoon workshop

• Software considerations for modeling and evalua
• Exercises in modeling - selecting the appropriate model for specific types of dataMethods of estimation: maximum likelihood; IRLS
• Constructing synthetic categorical response models
• Constructing models

Back to top

Method of Instruction

Lecture/discussion of subject material; PM: on-hands directed computer use applying methods learned in morning session to simulated and real data. Stata primarily used for examples.

Back to top

Prerequisites

A basic knowledge of linear models; some background with generalized linear models desirable.

Back to top

The Principal Lecturer

Joseph M. Hilbe is an Adjunct Prof. of Statistics at Arizona State University, Solar System Ambassador with Jet Propulsion Laboratory, California Institute of Technology, and Emeritus Professor at the Univ. of Hawaii. A Fellow of the American Statistical Association and elected member of the International Statistical Institute, Prof. Hilbe is one of the leading statisticians in the area of discrete response regression models, authoring 2 editions of the bestseller, Negative Binomial Regression (2007, 2011, Cambridge Univ. Press) and bestseller Logistic Regression Models (2009, Chapman & Hall/CRC), in addition to multiple editions of several other popular texts on statistics.

Recently, Prof. Hilbe co-authored the third edition of the Stata guide: Generalized Linear Models and Extensions.

Back to top

Prices

Cost (per participant):

Commercial / Government	$1400.00
Academics / Non-profit Research	$1050.00
Student registrations	$550.00

• A 20% discount is applied to early registrations (registrations made more than 6 weeks in advance of the course start date)
• All costs exclude local taxes, where applicable
• All costs exclude local taxes, where applicable
• Late Registrations: Registrations made within 6-weeks before the start of the course
• Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrollment)
• Additional discounts are available for multiple registrations
• Cost includes course materials, lunch, refreshments and the use of computers (please advise us if you have any dietary requirements)

The number of delegates is restricted. Please register early to guarantee your place.

If you need assistance in locating hotel accommodation in the region, please notify us at at the time of booking.

Back to top

Registration

We welcome delegates to find out more and register for the course by contacting our sales and training team either by email: info@timberlake-consultancy.com, phone: +1 908 686 1251 or by filling out an online registration form.

Back to top

Terms & Conditions

Payment of course fees required prior to the course start date.

Registration closes 5-calendar days prior to the start of the course.

• 100% fee returned for cancellations made over 28-calendar days prior to start of the course
• 50% fee returned for cancellations made 14-calendar days prior to the start of the course
• No fee returned for cancellations made less than 14-calendar days prior to the start of the course

Back to top

Return to:  Training Calendar  |  Home