Last revised: December 4, 2008
 

  Final:

• The final is due Friday, December 12, 2008 by 4:30pm. Your final/project can be turned into my mailbox in the Education building, Psychology building or to me in person. If you include a self addressed stamped envelope (large enough for your final/project to fit in) with campus address, I will return your exam/project with comments and grade.
• Projcts: for those of you doing a final project, here is a description of what to include in the final project.
• Exams: For thos of you doing a final exam, below is the exam and data set that you will need:
  • Final exam.
  • Data for the final exam.

• Syllabus (2008).
• Course log Up-dated December 4, 2008.

• 12/4/2008:
  • All homework keys and corresponding sas programs are on the web.
  • Sometime in the near future, I'll post notes on random effects models for count data (i.e., Poisson (loglinear) regression, Negative Binomial and Zero inflated models).
  • ICES will be distributed either Dec 4 or last day of class---come with ideas for improvements.
• 11/13/2008:
  • Link to homework 5 fixed.
  • Computer code created during today's lab is online (look under computer lab 4)
  • Answer key for homework 4 is linked.
• 11/11/2008: We will be in lab again this Thursday. If you came to the first session on Tuesday, come to the first session on Thursday. If you came ot the 2nd session Tuesday, come to the first session on Thursday. (The sessions left off at different places).
• 11/10/2008: The next computer lab is Tuesday November 10. There are two sessions 9:00-10:30 and 10:30 -12:00. Given that the 2nd was a bit crowded last time, I'ld suggest more come to the earlier one. The handouts, SAS, and homework are all posted.
• 11/3/2008:
  • Office hours this week will be on TUESDAY Nov 4th from 1-3.
  • SAS v 9.2 is available. It has much easier to use graphics and can do lots of things easier than was possible in v 9.1.
  • 10/30/2008:
    • Notes online are correct...they're messed up on my laptop.
    • Note that some of the titles on figures for exploring random effects for NELS are incorrect.
  • 10/21/2008:
    • Homework 4 will be due Thursday Oct 30th so that if you have problems or questions, you can see me during office hours on Wednesday.
    • SAS code from lab 3 (both sessions) is linked down below.
  • 10/20/2008:
    • The next computer lab, computer lab 4, is Tuesday, October 21. The computer lab notes and homework 4 are available below. As in previous labs, there will be two sessions: (1) 9:00am-10:30am and (2) 10:30-12:00. Come to just one.
    • The SAS code from computer lab 2 will be available tomorrow morning before lab.
    • The answer key for homework 3 will be posted tomorrow morning before lab.
    • I fixed the title page of notes on inference for random effects.
  • 10/13/2008:
    • The next computer lab will probably Thursday. I will decide for sure Tuesday...depends whether we finish inference notes or not.
    • I up-dated the next set of lecture notes (inference for random effects). If you have printed these out, they are bascially the same, but there are some changes which you can note in class.
  • 9/29/2008:
    • Instructions for computer lab #2, which will be Thursday Oct 1, is online.
    • Homework #3 is available (this goes with lab #2) and is due Thursday Oct 16.
    • The answers and sas code for homework #2 are available below.
    • I up-dated lecture notes on random intercepts and slopes and the ones on Estimation.
  • 9/26/2008:
    • Next computer lab (#2) will be next Thursday, October 1.
    • I will be editing notes on estimation (and random intercepts and slopes) to remove known typos.
  • 9/18/2008: Zhushan's Li's e-mail address is incorrect on the syllabus. Her address is zli10@illinois.edu .
  • 8/9/2008:
    • SAS code under random intercept models and SAS for HLM were "cleaned" up.
    • Computer Lab 1 will be Thursday Sept 11. Come to rm 15/17 in Education Building for either the 9-10:30 or 10:30-12:00 session.
    • Computer Lab instructions and data are posted on this site under Computer Lab 1.
    • Homwork 2 which goes with this computer lab is also posted.
  • 8/28/2008:
    • Homework 1 is available and is due Thursday Sept 4th (in class).
    • Introduction to SAS sessions will be held in rm 15/17 Education Bldg. The dates and times are Thursday Sept 4th 9:00-9:50am and Friday Sept 5th 4:00-4:50pm. Attendence is optional and you only need to attend one of these. The handout to be used in the lab are below (under lecture notes).
  • 8/18/2008: New syllabus is posted.
  Lectures Notes (I will be re-doing some of the SAS programs):
  • Introduction.
    SAS programs that generated (most of) the statistics and graphs in the lecture notes:
    • Juinor School Project..
    • Hypothetical longitudinal example
    • Two schools from NELS88
  
  
  • Models for clustered data: Fixed and random effects ANOVA and multiple regression. SAS code that produced statistics and graphics given in lecture note
    • NELS data for 10 schools. Run this program before the next one. You will have to change the directory for libname for your machine.
    • Generates statistics, fits models & produces graphics. You will have to change the directory for libname for your machine.
  
  
  • Random Intercept Models.
    
    
    • ANCOVA.sas. Fits ANCOVA model to NELS88, N=10 data (includes centering a variable, model fitting using GLM, and SAS/GRAPH of model).
    • hsb1.sas. Creates SAS data set of level 1 data for the High School and Beyond data.
    • hsb2.sas. Creates SAS data set of level 2 data for the High School and Beyond data.
    • hsball.sas. Merges level 1 and level 2 high school and beyond sas datasets.
    • betwithin.sas. SAS/GRAPHS for looking between and within variability of SES in the high school and beyond data.
    • randomintercepts.sas. SAS PROC MIXED and fitting random intercept models (includes centering SES)...and some graphics.
    
    
  • SAS for HLM.
    These will be used in lecture (they can also be used to reproduce the models for HSB data in the lecture notes on random intercept models):
    • HSB1 data. (level 1 data -- students)
    • HSB2 data (level 2 data -- schools)
    • SAS code to be discussed in lecture.
    • How to simulate multilevel data
    • Using SAS assist for graphics.
    • Using SAS insight. (interactive data analysis)
    This is from the introduction to SAS session:
    • Handout: Introduction to SAS by Example.
  
  
  • Random Intercept and Slopes Models. (up-dated Sept 29, 2008 --- I removed known typos, changed color to be more visible and incorperated "extra notes" into the lecture)
    
    
  • school23.sas. SAS program that creates SAS data set for NEL88 data for N=23 school.
  • NELS23.sas. SAS program that fits various random intercept and slope models to the NEL88 data for N=23 school.
  • Centering & NELS data. Illustrates effects of different kinds of centering -- NEL88 data for N=23 school.
  • SAS examples discussed in lecture.
  
  
  • Estimation of Marginal Model. (up-dated Sept 29, 2008)
  
  
  
  • Statistical Inference: Marginal Model.
  
  
  • SAS commands for ddfm (Simulation to show what different choices for df yield).
  
  
  • Statistical Inference: Random Effects.
  
  
  • SAS commands for mini-study on micro sample size on U's.
  • SAS commands for mini-study on macro sample size on estimates.
  • SAS commands for mini-study on effects of non-normality onf the distribution of EB estimates.
  • SAS program and EB estimates of U's.
  • Using SAS/Insight. Interactive data analysis and exploration (great for looking at data).
  • Using SAS/ASSIST to produce graphics.
  
  
  
  • Model Building. (these have been up-dated through page 168)
    • eda.sas SAS program including commands for exploratory data analyses (SAS/GRAPH, R^2meta, R^2_j, means structure, etc).
    • Simulations.sas. SAS program running first simulation and exploration of random structure.
    • Simulation_long.sas. SAS program running second simulation and exploration of random structure. This has a different sigma^2's and tau's.
    • New Variance EDA.sas. Exploratory data analyses of random structure for example given in class.
    • SAS v9.1 experimental diagnostics..
  
  
  
  • Longitudinal Data Analysis
    • Lecture notes on Longitudinal Data and HLM.
    • Lecture notes on Serial Correlation..
    • HLM for Riesby data. (data from Hedeker web-site plus my analyses using it).
    • Error Structures Simulation:
      • Random Effects Only.
      • First Order Auto Regressive, AR(1).
      • First Moving Average, MA(1).
      • First Order Auto Regressive Moving Average, ARMA(1,1).
    
    
    
  • Logistic Regression.
  • Longitudinal study on depression. (data from Agresti, 2002)
  • Longitudinal study on respiratory infections. (data from Skrondal & Rabe-Hesketh,2004)
  • Simmulation study & demonstration.
  • Rasch and 2pl model fit to LSAT6.
  • Rasch and 2pl model fit to General Social Suvery Vocabulary items with covariate. (This example will be discussed in class but it is the not in notes).
  
  Computer Lab Sessions:
  
  • Computer Lab Session 0: Introduction to SAS in GRICL, rm 15/17 Education Building.
    • HSB1 data sas file (level 1 data -- students)
    • Handout: Introduction to SAS by Example
    • Using SAS assist for graphics.
    • Using SAS insight. (interactive data analysis)
  
  
  • Computer Lab Session 1: rm 15/17 Education Building, Sept 11.
    • SAS program and data.
    • Computer Lab instructions.
    • SAS program created during the computer lab.
    • SAS program that does it all.
  
  
  • Computer Lab Session 2:
    • SAS program and data for Lab 2.
    • Computer Lab instructions & description of data.
    • SAS program that does it all.
  
  
  • Computer Lab Session 3:
    • Computer Lab instructions. We will use data and your programs from previous labs. (code will be posted right before the lab).
    • SAS commands written during lab session 1 (9:00-10:30).
    • SAS commands written during lab session 2 (10:30-12:00)....basically the same as session 1.
  
  
  • Computer Lab Session 4:
    • SAS program needed for computer lab 4.
    • SAS MACRO that draw a random sample of data.
    • Computer Lab instructions for Prelimnary EDA.
      SAS graphing handouts for preliminary fixed effects structure:
      • Plotting Data for each macro unit and displaying the graphs on a single page.
      • Plotting Regressions for each Macro Unit in a Single Graph.
      • Plotting Overall Mean Values for Ordinal Variables.
      • Plotting Mean Values for Ordinal Variables for Each Macro Unit all in a Single Plot.
      • Plotting Mean Values for Numerical Explanatory Variable for Levels of a macro variable in a Single Plot.
      • Computing R2 and R2META.
    • Complete SAS code for lab. (12/4/2008)
    • Some SAS code for exploring preliminary random effects structure
    • SAS code from lab session 1. (11/13/2008)
    • SAS code from lab session 2. (11/13/2008)
Homework

• Homework Number 1:
  • Homework assignment 1. Due Thursday Sept 4, 2008.
  • No Answer Key for this one needed.
  
  
  
• Homework Number 2:
  • Homework assignment 2. Due Thursday Sept 18, 2008.
  • Answer Key.
  
  
  
• Homework Number 3:
  • Homework assignment 3. Due October 16, 2008
  • Answer Key
  • SAS code for solutions
  
  
• Homework Number 4:
  • Homework assignment 4. (due Thursday Oct 30, 2008)
  • Answer key. (linked)
  • SAS forHomework assignment 4. (linked).
  
  
• Homework Number 5:
  • Homework assignment 5. (due Thursday Nov 20).
  • Parital Answer key.
  • SAS code for this homework.
  • SAS code for exploring random effects (wasn't required for homework but could be useful for future).
  
  
• Homework Number 6: Probably not one this year.....


Example SAS Programs (ascii/text format): Examples from Snijders & Bosker using SAS
• MLbook.sas. Create SAS data for examples in Chapters 4 and 5.
• Ch4_examples.sas. Example 2-level analyses from Chapter 4 (random intercept models).
• Ch5_examples.sas. Example 2-level analyses from Chapter 5 (random intercept and slopes).
• Ch12_examples.sas. Examples analyses from Chapter 12 (longitudinal data analysis), including creating sas dataset.
• Examples from Chapter 4 of Kreft & de Leeuw (provided and written by Carol Nickerson):
• School23.sas. SAS code that creates data set and fits models reported in Kreft & de Leeuw.
• school23.dat. Raw data file that is used as input to school23.sas.

• Ones specific to multilevel modeling:
• Centre for Multilevel Modelling. This site includes trainting materials, publications, reviews of multilevel software, data sets, a BBC audio program featuring Harvey Goldstein, and more..
• Tom Snijders' multilevel web-site. This has data & various material that's used in Snijders & Bosker An Introduction to Basic and Advanced Multilevel Modeling as well as other multilevel stuff.
• Scientific software international home page. Student version of HLM program can be downloaded from this site.
• NELS88 data: various data sets used in Kreft & de Leeuw (Introducing heirarchical linear modeling)
• Using SAS PROC MIXED to fit multilevel, heirarchical models, and individual growth models. Downloadable paper by Judith Singer. Other papers also downloadable.
• General ones:
• CIforP.f: A FORTRAN program that computes large sample confidence intervals for a proportion.
• 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.