General Information :

• Syllabus (2010).
• Course log. A record of what we actually do (2010).

• 1/4/2010: Lecture notes through Exact Tests except those on ordinal association have been up-dated.
• 1/7/2010: Change of location: Class will meet MW 10:00 - 11:50 am room 42 Education.
• 1/8/2010: Lecture notes on ordinal association for 2-way tables up-dated, as well as examples for 3-way tables.
• 1/14/2010: Furlough Days (i.e, I'm unavailable and am not suppose to work): Jan 22, Feb 26, Apr 2 and May 10.
• 1/14/2010: Class is full (at least last time I checked). I've started a waiting list. Contact me if you want to be on the list.
• 1/21/2010:
  • Bring laptop to class on Wednesday (preferablely charged given only limited number of outlets).
  • Homework #1 is posted down below
  • There will be a guest lecturer Wednesday Feb 24th.
• 1/25/2010: Lecture notes through Introduction to GLMs for binary data have been up-dated.
• 1/25/2010: Opps. I put the wrong due date for homework 1: the CORRECT data is Feb 3 in class
• l/18/2010: The link to instructions for remote login can be found at https://wiki.cites.uiuc.edu/wiki/pages/viewpage.action?pageId=44931949 . Before class on Monday, try to login to applications.education.illinois.edu
• 2/1/2010:
  • Office hours Tuesday afternoon are canceled. I'll be available after class on Wed.
  • I added a guide for writing homework (from one of my other classes but it also pertains to this one): Homework writing guide
  • Our tech guys are working hard to get the remote access to work properly --- they're highly motivated to make this work. In the meantime, thanks for you patience!
  • Next homework is available
• 2/4/2010: Answer key and SAS for homework 1 is linked.
• 2/8/2010: Since we have not covered the material for Problem 3 on homework 2, problem 3 (2.30 in the text) is not due this week. The problems that are due this Wed (2/10) are 1, 2, and 4.
• 2/20/2010:
  • Bring laptops to class on Wed. You'll learn how to do what you'll need for...
  • Homework 4 is now posted.
  • Answer key for homework 3 and sas code are linked.
• 3/29/2010: My office hours tomorrow will be in rm 437 Psychology bldg.

• Introduction.
  
  • Poisson distribution: World Cup Soccer, 1994.
  • Poisson distribution: World Cup Soccer, 1998.
  • Binomial example: Heights of candidates for US President..
  • Figure of likelihood of binomial: R code for the candidates for US President. (plain text file, .txt)
  • For the peer nominations of bullies see Lecture below on Poisson regression.


• Introduction to 2-way tables.
  
  
• Remote login and Introduction to SAS.. If possible, you should bring a (charged) laptop to this lecture.
  • hsb-data.sas.
  • Using SAS assist for graphics.
  
  
• Chi-squared tests.
  
  • Test of Independence: FECHLD X MAPAID (GSS 1994 data). (revised 2/3/2010 to show how to save standadized residuals to sas data set and then create a table of them).
  • Test of Independence: Admissions scandal.
  • Test of homoegeneous distributions: French skiers and effectiveness of vitamin C in preventing colds.
  • Need to add sas for example in lecture notes on partitioning chi-square here


• Tests of ordinal association.
  
  • Two "Likert" type items: FECHLD X MAPAID (GSS 1994 data).
  • A 2 x J table with orderd columns: Gender by Prestige using different scores.
  • A 3 x 3 table with with bad & good scores: School of Psychiatric Thought by Origin of schizophrenia (Agresti, 1990).
  • Power computation and plots: Power computuation.
  • Test for trend: Cochran-Armitage of Framinham heart study data.


• Exact tests for small samples.
• Fishers exact test: Admissions scandal.


• Three-way tables.
  • Conditional indpendence & marginal dependence: Cal graduate admissions
  • Conditional independnece & marginal dependence: Boy Scouts (hypothetical).
  • Conditional independence & marginal dependence: Blue collar workers x management x supervisor.
  • Conditional dependence & marginal independence: (Hypothetical) DIF.
  • Conditional dependence & marginal dependence: Age x Smoking x Breathing Test result.
  • Homogeneous association: Attitude toward media x year x race
  • Hurricane_Katrina


• Introduction to Generalized Linear Models (GLMs).
  
• Supplemental reading on GLMs: Draft Chapter on GLMs from Anderson, Verkuilen & Johnson (in preparation). Applied Generalized Linear Mixed Models.
• MatLab:
  • glmshow.m: MatLab m file from Peter Dunn's web-site that illustrates GLM regression for normal, Poisson and Gamma distributions with identity, log or reciprocal links and choice of diserpersion parameter.
  • glmlab (Peter Dunn)
• R (or S-plus): glm package.
• SAS examples from lecture notes:
  • Example of a variety of GLMS: T-cell and Hodgkin's disease.
  • SAS graph used to make figures in lectures: Step and S shaped functions.
    
  • More SAS graph (& data steps): Plotting cummulative distribution functions (normal & logistic).
    


• Introduction to GLMS for Dichotomous data
  
• Linear probability, logit & probit fit to grouped data: High School and Beyond.
  Note: you need to first run the program that creates the data set (i.e., hsb-data.sas). For a description of the variables, HSB coding.
• SAS_genmod_demo.sas. This was described in class. It shows how to fit linear probiability, logit and probit models using PROC GENMOD, as well as saving fitted values to a sas file and using SAS graph to plot results.


• Poisson regression
  
• Poisson regression with transformation of x: Deaths due to AIDS.
• Poisson regression & outliers: Crab data.
• Poisson regression with a few twists: Lung Cancer.


• Inference, modeling checking, and fixes for when things go wrong..
  
• Deaths due to AIDS.
• Lung Cancer.
• Crab data.
• SAS program from lecture 2/28/2007 (show how to fit Poisson regression models, save fitted values and other statistics, plot data & fitted line using SAS/GRAPH
• SAS: Bully nominations vs self report.



• The Basics of Logistic Regression
  • Logistic regression and model checking: High School & Beyond.
  • Regression diagnositics: ESR data.
  • SAS/MACRO (& example) for computing Range of Influence statistics: RangeInfluence.sas



• Multiple logistic Regression
  • High School & Beyond.
  • Excel file of Titanic passenger data..
  • SAS program that imports data (you need to change path to where you save the data).
  • SAS program that analyzsis titanic data . (This program is "hanging" my computer. Once I have it fixed, I'll post it).



• Log-linear Models
  • GSS 1992 Presidential Election
  • Blue Collar Worker data and how to compute the dissimilarity index in SAS



• Model Building for Log-Linear & Logit models
  • Wickens Olzak data with SAS code (graphical models and linear by linear)
  • HSB example of linear by linear & uniform association models
  • SAS program showing effect of sampling 0's (hypothetical from Wickens)
  • Health concerns by genders (data from Fienberg). How to handle structural zeros & include indicators for specific cells
  • Fitting RC(1) to HSB using NLP...with & without ordinal restrictions, and other models too.



• Logit Models for multicategory variables
  Extra reading: This site:
  • Anderson & Rutkowski (2008). Multinomial Logistic Regression. In Osborne "Best Practices in Quantitative Methods".
  • Anderson (in press). Categorical Data Analysis with a Psychometric Twist. In Milsap & Maydeu-Olivares "The Sage Handbook of Quantitative Psychology". 311-336.



• Models for matched pairs

• Homework writing guide



• Homework 1
  • Homework assignment 1. (due Feb 3--- not Jan 27)
  • Answer key for homework 1.
  • SAS program for problem 1 (Agresti 1.8).
  • An alternative solution to 1.8 using logit models. (I don't expect you to understand this until later in the semester).
• Homework 2
  • Homework assignment 2. (due Wed, Feb 10---Do no do problem 3 (2.30 in the text)
  • Answer key for homework 2.
  • SAS for Agresti (2007) 2.19.
  • SAS for Agresti (2007) 2.27.
  • SAS for Agresti (2007) 2.30. (moved to next homework assignment)
• Homework 3
  • Homework assignment 3. (due Wed Feb 17)
  • Answer key for homework 3.
  • SAS for Agresti (2007) 2.30.
  • SAS for Agresti (2007) 2.33.
  • SAS for Agresti (1996) 3.8 and 3.9 (i.e., last two problems of the assignment)
• Homework 4
  • Homework assignment 4. (due Wed Mar 3)
  • Answer key for homework 4.
  • SAS problem 1.
• Homework 5
  • Homework assignment 5. (due Wed Mar 17)
  • Crab data (plus a little SAS).
  • soccer data (plus a little SAS).
  • Answer key.
  • SAS for Agresti (2007) 3.11 and 3.12.
  • SAS for Agresti (2007) 3.13, 3.14 and ZIP. Note: dist=zip in GENMOD requires SAS v9.2 or later.
  • SAS for Agresti (2007) 3.18.
• Homework 6
  • Homework assignment 6. (due Wed April 7)
  • Data for problem 1.
  • Answer Key.
  • SAS for problem 1 (small pox).
  • SAS for lefthanded presidents.
  • SAS for NY Times data.
• Homework 7
  • Homework assignment 7. (Due Monday April 26)
  • Answer Key.
  • Sas for 7.4.
  • SAS for 7.15.
  • Table 5.12 (problem 4).
• Final Exam or Project
  • If you are doing a project here is a description of what to include in your project.
  • If you are taking the final, (comming soon)
    • Final Exam. (due May 7, 5pm)
    • Data for Problem 2.
    • Data for Problem 3.
    • Data for Problem 4.
    • Data for Problem 5.

• Linear, logit and probit models of probiblities: model the probability of having attended academic program as a function of achievement test scores.
  • HSBdata and program for binary models and plotting.
  • SAS program.
  • Output from program
• Dealing with overdispersion (SAS options and negative binomial): Poisson regression example of number of deaths due to AIDs.
  • SAS program.
  • Output from program in text format
  • Output from program in postscript format
  • Maybe add ZIP example
• Multiple logistic regression
  • SAS program to create HSB data set
  • SAS program that performs multiple logistic regressions, etc.
• Log-linear models and SAS:
  • Computing the dissimilarity index
    • SAS program using Blue Collar data. (fits loglinear data, saves fitted values, merges output files, creates components of D index, and then sums to get the dissimilarity index).
    • SAS output.
  • Log-linear/logit model connection
    • SAS program for 4-way table (Marital status x Gender x PMS x EMS). Two log-linear models are computed including one that is equivalent to a logit model, which is also fit directly as a logit model.
    • SAS output.
• Example of linear by linear, uniform, and nominal by ordinal association models using SAS (high school and beyond SES X HSP).
  • SAS input and output. (in postscript format)
  • SAS input. (in text format)
• Example of effect of sampling zeros used in lecture.
  • SAS input and output. (in postscript format)
  • SAS input. (in text format)
• Generalized CMH tests for ordinal x ordinal, nominal x ordinal, and general association.
  SAS input and output. (in text format)
• Example of baseline/multinomial logistic response model, (output is in postscript format).
  • baseline handout
  • SAS program that fits baseline model and generates figures of fitted and observed values
• Likelihood ratio tests of the equality of parameters over response options in the multinomial response model, (output is in postscript format).
  • Multinomial logistic LR tests
  • SAS program of Multinomial logistic regression and LR tests
• Examples of conditional logit response model, (output is in postscript format).
  
  • Chocolate candy
  • Five brands
  • SAS program for Chocolate candy
  • SAS program ofr Five brands

• CIforP.f: A FORTRAN program that computes large sample confidence intervals for a proportion. For PC computers, a execultable version of CIforP (i.e., already complied)



• pvalue.f: A FORTRAN program that computes p-values and (bonferroni) critical values for the standard normal, chi-squared, t, and F distributions (and for correlations). For users of PC type computers, pvalue.exe is an executable (i.e. already compiled) program.



• Supplement to Agresti (2002, 2007): Software for categorical data (SAS, R/S-splus, Stata, others)



• Appendix to Agresti (2007): SAS and Data sets from Agresti (2007) and links to R and S-plus materials.