Welcome to The Multivariate Analysis of Categorical Data!  On this site are topics, readings, and dates for assignments for EDF 6937-05 Spring 2017. Watch this website over the semester for more information. Need more information NOW? Please contact me via email: slosh@fsu.edu

Prerequisites (in addition to a basic statistics course, e.g., EDF 5400 or equivalent): a course in multiple regression OR the general linear model, OR analysis of variance or the equivalent (e.g., EDF 5401, EDF 5402, EDF 5406 etc)

MAIN TEXT: Alan Agresti, An Introduction to Categorical Data Analysis. SECOND EDITION! (Wiley, 2007)

Because it differs considerably from the first edition, be sure to get the SECOND edition of Agresti.
There are several alternatives to saving money on Agresti. I'll go over them in class!
 

NOTE: A more expanded version of Agresti, which is different and more mathematical, can be found at: Alan Agresti, Categorical Data Analysis. THIRD edition, Wiley: 2012.

Other readings from: Nigel Gilbert, Analyzing Tabular Data: Loglinear and Logistic Models (1993; ISBN = 1857280903; to be provided for you)  and

Online Course Guides

The Agresti book can be found at Bill's (both stores) and the FSU Bookstore. Used copies ARE available at Bill's.
It is quite possible that you can find used copies online at Amazon and other sites for a good deal.
I will make copies of the Gilbert chapters for you.

ALL MY COURSE LECTURES will be placed on the Internet and linked in with each course topic.

Course guides will be keyed to the readings. See the top of each Guide as it is posted.

The lecture urls have the general form of:

Please type in course urls EXACTLY. There is no "www" in these urls.

Each Guide is linked to every other Guide so that it is easy to navigate from one to another.
Course Guides are also linked to course topics and will be placed on our class Blackboard site (please see below).

Although I may not cover all the material in each one during class time, you are responsible for ALL the material in each guide. That is why they are on the Internet.

I recommend that you read my online guides FIRST. They emphasize the portions of the material that I think are the most important for this course. I think it will be easier for you to understand the texts after you have read the associated guide.

Some of the material in the guides will be covered during class. However, class time will also be used for instruction related to each assignment, demonstrations, presentation, review, and assignment feedback.
 

Here is information about  assignments, due dates, and course weights.

There will be four short equally weighted exercises.  While each exercise will focus on the immediately prior units, please be advised that this material is cumulative in nature.

Exercises have several purposes:

To familiarize you with terminology, basic operations, and associated computer programs.

To help practice your basic analysis and results interpretation skills. For example, logistic regression coefficients are often used and equally often misinterpreted.

To alert you to common problems that occur with different kinds of analyses and ways to solve these problems.

All four exercises put together will count a total of 40% toward your final grade.

Details on each assignment are posted to our course WEB site prior to the due date.

As exercises and exercise feedback sites are created and posted, watch the space at the top of the Guides for information and links.

An analytic paper will count 40% toward your final grade.

A presentation based on your analytic paper will count 20% toward your final grade.

In the paper, you will analyze data using course material and interpret your findings. The general format of the paper will resemble a journal article.

You may use your own data, data from your major professor, or one of the many data sets I have available.

I use plus and minus grading, throughout and for final grades.

If I think you are having trouble with the material, I will alert you immediately and I expect you will seek remedial help as quickly as possible. If you receive such an alert, please take it very seriously. Please do not tell me that you "really understand the material" and fail to seek help. I issue such alerts when the work makes it obvious the student DOES NOT understand the material.

(You will be forwarded to the new, more complicated url BUT the above url works and is easy to remember.) Enter your FSU username (USERNAME ONLY!) and password to log in. For example, I would enter "slosh" ONLY and omit the "@fsu.edu" part. Then click on:

to enter our site. Browse the diverse categories that are available.

Each Guide (lecture) will have links posted at the top to the Course Overview, Syllabus, and all prior course Guides. This makes getting around the course material easy. Watch the top of each Guide for announcements about assignments, generic feedback, and any schedule changes.

When sites are under construction, there will be a warning sign at the top. Do not copy those sites until construction warnings are removed.
 

There may be some variations from this syllabus. Please check back weekly and watch Blackboard for any announcements.

DATES	TOPICS TO BE COVERED	READINGS & ASSIGNMENTS
January 10-17	Introduction: Issues in Modeling Causal issues in experimental, nonexperimental and observational data and their implications for models Some basic distributions	Guide 1 Gilbert, preface and pp. 1-7 Agresti, pp. 1-6 Skim Agresti Chapter 11 for the history!
January 17-24	Bunches of basics: terminology ; Odds-Ratios; MLEs; iteration; Chi-square as goodness of fit; poisson and multinomial distributions. The basic two-way (2 X 2) cross-tabulation table recast	Guide 2 (beginning glossary) Gilbert, pp. 13-24; 27-33 Agresti, pp. 6-15; 21-41; 49-54
January 24-31	Review General Linear Model Basic loglinear models.  A probabilistic model for table cell counts.  Begin with two way table, extend initially to three way (2 dichotomous, 1 not, then to multinomial). Frequency equations; transformed to log-linear equations.	Guide 3 (The 'Lowly' 2 X 2 Table) Gilbert, pp. 39-49; 58-62 Agresti, pp. 65-75 (skim examples!) 84-90; 204-228
February 7	EXERCISE 1	Basic terminology exercise
February 7-14	N-way tables Model construction and model testing in the loglinear model	Guide 4 Gilbert, pp. 66-77; 101-110; 147-156 Agresti, pp. 137-152
February 14-21	Introduction to programs and analysis:  Examples and demonstrations (output interpretation)	Guide 5
March 7	EXERCISE 2	Program 1 and writing a loglinear equation
February 28-March 7	The logit model.  Transformation from the loglinear to the logit model.  Transform equations to logit model.	Guide 6 Gilbert, pp. 115-125 Agresti, pp.221-228
March 13-17	No class--Spring Break
March 21	Issues in testing logit models.  Demonstrations
March 21	Paper precis	What's your topic? What're your data? Information for the analytic paper
March 28	EXERCISE 3	Nonhierarchical loglinear models
March 28-April 4	The special case of logistic regression. Dichotomous and polytotomous dependent variables.  Poisson, binomial and multinomial regression. More programs: Multinomial logistic regression  Power	Gilbert, pp. 131-142 Agresti, pp. 99-121 160-162 173-197
April 11	EXERCISE 4	Loglinear to logit transformation Running a logit model program
April 18	First draft analytic paper (allows me to get it back to you in time to revise)  Presentations begin (April 18 & 25)	Please submit paper draft through turnitin onBlackboard  PRESENTATION INFO
April 4-25	Various extensions and special cases: Model Fitting Ordinal response variables versus nominal models;  Sparse data; Quasi independence;  Structural versus sampling zeros Odds and ends	Guide 7 Agresti, pp. 41-45 Gilbert, pp. 167-175 Gilbert, pp. 82-95; 159-164 Agresti, pp. 152-160; 189-196; 228-232; 261-262 297-318 Guide 8
May 3 NOON	Analytic paper due FINAL DUE DATE!! submit through turnitin	Paper Guide

A LECTURE (AND ASSOCIATED MATERIALS) WILL BE LINKED WITH EACH TOPIC AS THE SEMESTER PROGRESSES.
 
 

OVERVIEW

This page was created with Netscape Composer.
There may be some minor changes as the semester progresses.
Your patience is appreciated.
Susan Carol Losh
December 31 2016
Welcome back!