Biostat 251 - UCLA (Spring 2017)


  • Instructor : Donatello Telesca
  • Lecture: MW 1:00 pm to 2:50 pm- HLT SCI 33-105A
  • Office hours: T 2:00pm  to 3:00pm - PUB HLT 21-254B 

Announcements

 


Homework


Schedule of Lectures

  • (4/02) Introduction - Preliminary Mathematical Notions 
  • (4/04) The Multivariate Normal Linear Model
  • (4/09) Testing General Linear Hypotheses
  • (4/11) Improved Estimation of Means and Covariances - Bayesian Analysis (slides.pdf, slides.Rmd
  • (4/16) Introduction to Longitudinal Data - Linear Mixed Effects Models (slides.pdf)
  • (4/18) Introduction to Longitudinal Data - REML + Bayes (slides.pdf)
  • (4/23) Introduction to Longitudinal Data - GLMM (slides.pdf)
  • (4/25) Introduction to Longitudinal Data - Hierarchical Models (slides.pdf, slides.Rmd)
  • (4/30) Introduction to Longitudinal Data - GEE (slides.pdf)
  • (5/02) Generalized Estimating Equations [See Manuscripts in the Reading List]
  • (5/07) Introduction to Graphical Models. Markov Properties. [Lectures on Algebraic Statistics, Ch 3]
  • (5/09) Midterm
  • (5/14) Hammersley-Clifford and Recursive Factorization Theorems. [Lectures on Algebraic Statistics, Ch 3]
  • (5/16) Structure Discovery in Graphical Models [Elements of Statistical Learning, Ch 17 - (book.pdf)]
  • (5/21) Linear Dimension Reduction 
  • (5/23) Class Cancelled
  • (5/28) No Class: Memorial Day Holiday 
  • (5/30) Introduction to Classification (Slides.pdf)
  • (6/04) Introduction to Clustering (Slides.pdf)
  • (6/06) Introduction to Statistical Models using Copula (Notes.pdf)

Coursework
6-7 HW Assignments 20%  
Midterm (05/09) 40%
Take-Home Final Due (06/14) 40%


Reading List

(Recommended Textbooks)

  • Anderson T.W., An Introduction to Multivariate Statistical Analysis. Wiley Series in Probability and Statistics. 
  • Izenman A.J., Modern Multivariate Statistical Techniques. Regression, Classification and Manifold Learning. Springer.
  • Seber G., Multivariate Observations. Wiley Series in Probability and Statistics.
  • Mardia, Kent and Bibby, Multivariate Analysis. Academic Press.
  • Rowe, Multivariate Bayesian Statistics. Chapman and Hall.
  • Diggle, Heagerty, Liang and Zeger, Analysis of Longitudinal Data. Oxford.
  • Hoff, P., A first Course in Bayesian Statistical Methods. Springer
  • Drton, M., Sturmfels, B and Sullivant, S. Lectures on Algebraic Statistics. Springer

 

(Longitudinal Data Analysis Textbooks)

  • Diggle, PJ, Heagerty, P, Liang KY and Zeger SL (2002). Analysis of Longitudinal Data. Oxford University Press.
  • Weiss R., Modeling Longitudinal Data. Springer Texts in Statistics.
  • Fitzmaurice GM, Laird, NM and Ware JH (2004). Applied Longitudinal Analysis. Wiley.
  • Verbeke, G and Molenberghs, G (2000) Linear Mixed Models for Longitudinal Data. Springer-Verlag.
  • Wakefield, J. (2012) Bayesian and Frequentist Regression Methods. Springer.


(Journal Articles)

Mixed Effects Models

  • Sartori, N. and Severini, T.A. (2004). Conditional Likelihood Inference in Generalized Linear Mixed Models. Statistica Sinica, 14, 349-360.
  • Breslow, N.E. and Clayton, D.G. (1993). Approximate Inference in Generalized Linear Mixed Models. JASA, 88, 125-134.
  • Liard, N.M. and Ware, F. (1982). Random Effects Models for Longitudinal Data, Biometrics, 38, 963-974.
  • Lindstrom, M., & Bates, D. (1988). Newton-Raphson and EM algorithms for linear mixed effects models for repeated measures data. JASA, 83,1014 1022.

 

GEE

  • Liang, K-Y. and Zeger S.L. (1986). Longitudinal Data Analysis Using Generalized Linear Models. Biometrika, 73, 12-22.
  • Prentice, R.L. (1988). Correlated binary regression with covariates specific to each binary observation. Biometrics, 44, 1033-1048.
  • Pepe, M. S. and Anderson, G.L. (1994) A cautionary note on inference for marginal regression models with longitudinal data and general correlated response data. Communications in Statistics - Simulation and Computation, 17, 1155-1171.
  • Zhao L. P. and Prentice R.L. (1990). Correlated binary regression using a quadratic exponential model. Biometrika, 77, 642-648.

 

Classic Multivariate Analysis

  • Eaton, M.L. and Perlman, MD. (1973). Non-Singularity of Generalized Sample Covariance Matrices. Annals of Statistics, 1 (4), 710-717.
  • Okamoto, M. (1973). Distinctness of Eigenvalues of a Quadratic Form in a Multivariate Sample. Annals of Statistics, 1 (4), 763-765.

 

Graphical Models

  • Jordan, M. I. (2004). Graphical Models. Statistical Science, 19 (1), 140-155.
  • Dawid, P. (1979). Conditional Independence in Statistical Theory. JRSS B, 41, 1, 1-31.
  • Lauritzen, S.L. and Spiegelhalter, D.J. (1988). Local Computations with Probabilities on Graphical Structures and their Application to Expert Systems. JRSS B, 50, 2, 157 - 224.
  • Arnold, B.C. and Press, J. (1989). Compatible Conditional Distributions. JASA, 84, 152-156.
  • Gelman, A. and Meng, XL. (1991). A Note on Bivariate Distributions that Are Conditionally Normal. The American Statistician, 45 (2), 125-126
  • Besag, J. (1974). Spatial Interaction and the Statistical Analysis of Lattice Systems. JRSS-B, 36, 192-236.  

Computing
Recommended computing for Biostat 251 will be based on the R programming language.
For more information please visit (http://cran.r-project.org/).