Lecture 2 (Wed., Jan. 12): Matrix review, multivariate normal review.
HW Assignment 1 Due Wednesday, Jan. 26.
Lecture 3 (Wed., Jan. 19): Start Ch. 4, models for longitudinal data.
Lecture 4 (Mon., Jan. 24): Split plot model in sas, other notation for longitudinal models.
Lecture 5 (Wed., Jan. 26): SAS glm with the repeated statement. Response to Feedback.
HW Assignment 2 Due Wednesday, Feb. 9
Lecture 6 (Mon., Jan. 31): Multivariate statistics via glm and the repeated statement and manova options (Ch. 6), restrictions of glm (Ch. 7).
Lecture 7 (Wed., Feb. 2): Introduction to modeling longitudinal data in proc mixed, covariance structure selection.
Lecture 8 (Mon., Feb. 6): "Noint" parameterization and "Difference" parameterization for dental data. Analysis for the dialyzer data, where pressure is measured at different values.
Lecture 9 (Wed., Feb. 8): Analysis of the hip replacement data, with missing response values, proc mixed parameters--contrast and estimate statements.
HW Assignment 3 Due Wednesday, Feb. 23.
Lecture 10 (Mon., Feb. 14): Consulting Example: Units over time within blocks and comparisons with standard ANOVA.
Lecture 11 (Wed., Feb. 16): Begin Ch. 9, random coefficient models.
Lecture 12 (Mon., Feb. 21): Random cofficient models, dental data and dializer data.
Lecture 13 (Wed., Feb. 23): Review for Mid-Term.
Mid-term Exam (Monday, Feb. 28). 11:30-1:15 (come early to class, and leave a little late). Covers Chapters 1-8. You may use one side of an 8.5 by 11 sheet of paper with hand-written notes during the exam. Bring a calculator.
Spring Break, March 7-11.
Lecture 14 (Mon., Mar. 14): Ch. 10. The general linear mixed model: linear terms that are either fixed or random, Best Linear Unbiased Prediction (BLUP) of random quantities.
Lecture 15 (Wed., March 16): More on BLUPS and EBLUPS. Weight lifting example.
HW Assignment 4
Due Wed., March 30.
Lecture 16 (Mon., Mar. 21): Testing of variance components.
Project Description, Data Set, Standard Code
Lecture 17 (Wed., Mar. 23): Ch. 11: generalized linear models, independent Y's. Poisson example.
Lecture 18 (Mon., Mar. 28): Ch. 11: glm's continued. Score equations and asymptotic variance. Binary, Poisson, and gamma examples
Lecture 19 (Wed., Mar. 30): Ch. 12: begin GEE, extension of glm's to longitudinal data.
HW Assignment 5
Due Wed., April 13.
Lecture 20 (Mon., April 4): Ch. 12, more GEE.
Lecture 21 (Wed., April 6): GEE examples: i) quitting smoking and ii) childhood obesity.
Lecture 22 (Mon., April 11): Student essays consulting example.
Lecture 23 (Wed., April 13): Student essays consulting example, proc genmod, cumulative logit.
Lecture 24 (Mon., April 18): Random coefficient models in binary logistic regression, schizophrenia example.
Lecture 25 (Wed., April 20): Overview of fitting continuous data models using schizophrenia example.
Lecture 26 (Mon., April 25): Review.
Lecture 27 (Wed., April 27): Project discussion.