Biostatistical Methods II:  Regression Analysis (Biometry 701)

Spring 2009

 

Description:  This is a one-semester course intended for graduate students pursuing degrees in biostatistics and related fields such as epidemiology and bioinformatics.  Topics covered will include linear, logistic, poisson, and Cox regression.  Estimation, interpretation, and diagnostic approaches will be discussed.  Software instruction will be provided in class in R and Stata.  Students will be evaluated via homeworks (55%), two in-class exams (35%) and class participation (10%).  This is a four credit course.

 

Textbook:  Applied Linear Statistical Models.  Kutner, Nachtsheim, Neter and Li.  McGraw-Hill, Fifth Edition

 

Prerequisites:  Biometry 700

 

Course Objectives:  Upon successful completion of the course, the student will be able to

    1.  Apply, interpret and diagnose linear regression models

    2.  Apply, interpret and diagnose logistic, poisson and Cox regresssion models 

 

Instructor:

Elizabeth Garrett-Mayer

Website: http://people.musc.edu/~elg26/teaching/methods2.2009/methods2.2009.htm

Contact Info:

 Hollings Cancer Center, Rm 118G

 

garrettm@musc.edu (preferred mode of contact is email)

 

792-7764

Time: Mondays and Wednesdays, 1:30-3:30
Location: Cannon 301, Room 305V

 

Lectures:

Date

Topic

PDF

Computing Reading Assignment

W Jan 7

Introduction to regression; simple linear regression (SLR)

lect1.ppt

R code Ch 1

M Jan 12

no class! Instructor at workshop in MD

 

   

W Jan 14

Linear model properties; software tutorial

lect2.ppt

  R-intro.pdf (supplemental)

M Jan 19

no class!  MLK Jr. Day

 

   

W Jan 21

Linear model properties; software tutorial

(see Jan 14)

  Ch 2

M Jan 26

Inferences and assumption checking in SLR

lect3.ppt

R code Ch 6

W Jan 28

SLR Diagnostics

lect4.ppt

R code  
M Feb 2 Diagnostics (continued);Correlation; Intro to Multiple Linear Regression lect5.ppt R code Ch 5
W Feb 4 Hypothesis testing in LR lect6.ppt R code Ch 2, Ch 6
M Feb 9 MLR     Ch 2, Ch 6
W Feb 11 Forms for predictors lect7.ppt R code Ch 8
M Feb 16 interactions lect8.ppt R code Ch 7
W Feb 18 F-tests and ANOVA lect9.ppt R code  
M Feb 23 F-tests and Coefficients of Determination lect10.ppt R code Ch 7
W Feb 25 Multicollinearity lect11.ppt R code Ch 7
M Mar 2 MLR Model Building lect12.ppt R code Ch 9
W Mar 4 MLR:  final comments lect13.ppt R code Ch 10
M Mar 9 NO CLASSES:  SPRING BREAK!      
W Mar 11 NO CLASSES:  SPRING BREAK!      
M Mar 16

no class! Instructor at meeting in TX

     
W Mar 18 MLR final comments (see W Mar 4)    
M Mar 23 Introduction to logistic regression lect14.ppt R code Ch 14
W Mar 25 Inference and link functions lect15.ppt R code  
M Mar 30 Likelihood ratio tests and deviance      
W Apr 1 Goodness of fit, Information criteria, lect16.ppt R code, Stata do  
M Apr 6 ROC Analysis (see lect16)    
W Apr 8 Logistic regression for case control studies lect17.ppt    
M Apr 13 Catch up day      

W Apr 15

Logistic regression for matched case control studies class canceled  enjoy doing your taxes!  

M Apr 20

Introduction to survival data lect18.ppt   http://jslhr.asha.org/cgi/reprint/42/2/432

http://www.walkerbioscience.com/pdfs/Survival%20analysis.pdf

W Apr 22 Survival analysis lect19.ppt    
M Apr 27 Cox regression lect20.ppt R code  
W Apr 29 Exam 2      

 

Datasets:

    Ischemic Heart Disease:  IschemicHeartDisease.csv

    Prostate Cancer Dataset:  Prostate.csv (codebook:  prostate.txt)

    ICU dataset:  icu.csv (codebook:  icu.txt)

    Kidney Dialysis:  kidneydialysis.csv

 

Homeworks:

    Homework 1.pdf       Due Mon    01/26/09

    Homework2.doc       Due Wed    02/04/09

    homework3.doc        Due Wed    02/18/09

    homework4.doc        Due Fri       03/06/09

    homework5.doc        Due Wed    04/08/09

    homework6.doc        Due Mon    04/20/09

    homework7.doc        Due Wed    04/29/09

 

EXAMS:

exam1.doc     Due Mon 03/09/09

 

Articles:

gillison.pdf:  Case control study of HPV16 and Oropharyngeal Cancer

hanley&mcneill.pdf:  Comparing AUCs for ROC curves based on the same data

chaves.pdf:  Nomograms for mobility disability

 

Computing: 

    R website:  http://cran.r-project.org/

    R tutorial:  R-intro.pdf

    Stata website:  http://www.stata.com/