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HSRP 734 Advanced Statistical Methods
Class Meets: 9:00 – 12:00 Thursdays, PP-II Room 211


Downloadable Course Files (most recent at top, horizontal rule divides first half of class from second):

Name: Date: Size:
extra topics.ppt  07/30/2008  391680 
HW 6 due 7-31.doc  07/23/2008  31232 
Eval PH assumptions.ppt  07/18/2008  411136 
HW 5 due 7-24.doc  07/17/2008  33280 
hw5data.sas7bdat  07/17/2008  17408 
CPH I - july 17.ppt  07/17/2008  478208 
uissurv.sas7bdat  07/17/2008  87040 
aml_example.sas7bdat  07/17/2008  5120 
aml_example_rev.sas7bdat  07/17/2008  5120 
smaller_aml.sas7bdat  07/17/2008  5120 
KM and log rank project july 10.egp  07/10/2008  92284 
HW 4 due 7-17.doc  07/09/2008  50688 
hw4.sas7bdat  07/09/2008  5120 
aml_example_orig.sas7bdat  07/09/2008  5120 
KM and log rank - July 10.ppt  07/09/2008  607232 
intro to survival analysis - july 3.ppt  07/09/2008  1041920 
eval PH example.sas  07/23/2007  2365 

exact.sas  06/18/2008  14322 
gee.sas  06/18/2008  13254 
HW3 solution key.doc  06/18/2008  166912 
Lecture 5 - Extensions.ppt  06/18/2008  235008 
match.sas  06/18/2008  1870 
poly2.egp  06/18/2008  218956 
poly2.sas7bdat  06/18/2008  25600 
HW1 solution key.doc  06/11/2008  67584 
HW2 solution key.doc  06/11/2008  136704 
ICW-diagnostics.egp  06/11/2008  241000 
chd3.sas7bdat  06/11/2008  25600 
ICW - Diagnostics.doc  06/11/2008  31744 
ICW - Model building.doc  06/11/2008  44544 
ICW-model building.egp  06/11/2008  314787 
chd2.sas7bdat  06/11/2008  17408 
Lecture4-Building Diagnostics 6-12-08.ppt  06/11/2008  1127424 
HW3.doc  06/04/2008  39936 
mistudy.sas7bdat  06/04/2008  17408 
mistudy_notes.doc  06/04/2008  24576 
chd.egp  06/04/2008  85741 
chd.sas7bdat  06/04/2008  9216 
Lecture3-Logistic Regression 6-5-08.ppt  06/04/2008  638976 
cmh.egp  05/28/2008  52930 
HW2.doc  05/28/2008  33280 
q2.sas7bdat  05/28/2008  5120 
chisq.egp  05/28/2008  44970 
or_rr.egp  05/28/2008  46723 
chisq.sas7bdat  05/28/2008  5120 
cmh.sas7bdat  05/28/2008  9216 
Lecture2-Chi square 5-29-08.ppt  05/28/2008  373248 
or_rr.sas7bdat  05/28/2008  13312 
Lecture1-Intro CDA Association Measures.ppt  05/19/2008  594944 
HW1.doc  05/16/2008  48128 
HSRP 734 Syllabus.doc  05/16/2008  40448 

Class

Content

Homework

22-May

1.1 Overview, Review of concepts
1.2 Categorical Data Analysis
1.3 Measures of disease occurrence & association



#1 Assigned

29-May

2.1 Chi-square analysis
2.2 Odd’s ratios, relative risk & attributable risk
2.3 SAS Lab


#1 Due
#2 Assigned

5-Jun

3.1 Simple Logistic Regression
3.2 Multiple Logistic Regression
3.3 SAS Lab


#2 Due
#3 Assigned

12-Jun

4.1 Model building in Logistic Regression
4.2 Logistic Regression Diagnostics


#3 Due

19-Jun

5.1 Advanced Topics in Logistic Regression
5.2 Review

 

26-Jun

1st Exam

 

3-Jul

6.1 Time to event data
6.2 Survival, hazard and related functions
6.3 SAS Lab

 

10-Jul

7.1 Kaplan-Meier & hazard function estimates
7.2 Log rank tests
7.3 SAS Lab



#4 Assigned

17-Jul

8.1 Cox Proportional Hazards Regression
8.2 Interpreting coefficients and confidence intervals
8.3 SAS Lab


#4 Due
#5 Assigned

24-Jul

9.1 Evaluating proportional hazards assumption
9.2 Model Diagnostics
9.3 SAS Lab


#5 Due
#6 Assigned

31-Jul

10.1 Advanced Topics in Cox Proportional Hazards Regression
10.2 Review


# 6 Due

7-Aug

2nd Exam

 


Instructors:

Gregory W. Evans, Assistant Professor & Section Head on Biostatistics
2nd Floor One Technology Plaza (OTP)
336-716-6016
gevans@wakehealth.edu
Office Hours: 2 – 4 pm, Thursdays

Thomas McCoy, Biostatistican III
23rd Floor Wachovia Tower
336-716-3483
tmccoy@wakehealth.edu
Office Hours: 9 am – 11 noon, Wednesdays

James F. Lovato, Biostatistican IV
23rd Floor Wachoiva Tower
336-713-4172
jlovato@wakehealth.edu
Office Hours: 1 pm – 3 pm, Wednesdays

Qiang (Peter) Zhang, Research Associate
23rd Floor Wachoiva Tower
336-716-5141
qizhang@wakehealth.edu
Office Hours: 1 pm – 3 pm, Mondays

Textbooks:

Kleinbaum DG, Klein, M (2002) Logistic Regression: A Self-Learning Text. 2nd
    Edition. Springer.

Kleinbaum DG (1996) Survival Analysis: A Self-Learning Text. Springer.

Grading:

1st Test             35%
2nd Test            35%
Homework       30%  (6 assignments worth 5% each)


 
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