University of Alberta

Course Guide for SPH 619 Winter 2016 (Campus)

[Biostatistics II] [Tuesday/Thursday: 10:30 AM to 11:50 AM] [Room: ED 170] Lab: Tuesday/Thursday: 9:30 AM to 10:20 AM (Lab: MSB 2-50) (TA will answer your questions on STATA; No formal Instruction)

Instructor: Dr. A. (Sentil) Senthilselvan Telephone: (780) 492 6505 e-mail: [email protected] (Prof. Gian Jhangri will assist me with teaching logistic regression)

Teaching assistant: Ms. Elham K Moez e-mail address: [email protected]

Course Description:

Regression methods used to analyze epidemiologic data with a special emphasis on practical applications in health sciences research. Topics include multiple linear regression, logistic regression, proportional hazards regression Prerequisite: SPH 519 or consent of the instructor.

Competencies

• Distinguish between the commonly used regression methods in biostatistics

Explain Analyze Interpret Conclude Explain Analyze Interpret Conclude Explain Analyze Interpret Conclude

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Uses multiple linear regression methods to analyse continuous data

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Uses multiple logistic regression methods to analyse binary data

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Uses proportional hazards regression methods to analyse censored survival data

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Uses purposeful selection method for model building

Explain Apply

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Demonstrates awareness of assumptions, strengths and limitations of key biostatistical methods

Explain

• Uses appropriate methods for assessing goodness of fit of regression models

Explain

• Uses statistical software to carry out

Explain Apply

regression analysis

Library

Explain

Apply Interpret

The University of Alberta library system’s website www.library.ualberta.ca details the range of services offered to students on and off campus. If you need further information or assistance, contact the Library's Electronic Reference Desk at www.library.ualberta.ca/ereference/index.cfm or call 1-800-2070172.

[SPH 619, Biostatistics II] 2016 Course Syllabus

University of Alberta, School of Public Health Page 2

Learning Resources

All required materials are made available through e-class. Lecture notes and reading materials will be provided (hard copies in class and electronic copies in e-class). You do not have to purchase any textbooks for this course. The books given in the references below are only for additional reading. Advanced biostatistical methods will be discussed without using complicated mathematical formulas. Power point slides and data examples used in the class will be provided. Office hours Instructor will be available after the class on Tuesday and Thursdays. Questions can be asked anytime in e-class anonymously (Instructor will usually answer within 24 hours) Audio recordings will be available in MP3 format for review in the e-class.

References Multiple linear regression 1) Kleinbaum DG, Kupper LL, Muller KE, Nizam A. Applied Regression Analysis and other Multivariable Methods. 4th Edition. Duxbury Press. Toronto. 2008 2) Dupont WD. Statistical Modeling for Biomedical Researchers: A simple introduction to the analysis of complex data. 2nd Edition. Cambridge University Press. 2009. Available online in the U of A Library: http://site.ebrary.com/lib/ualberta/detail.action?docID=10277518 Logistic regression 1) Hosmer DW, Lemeshow S, MAY S. Applied Logistic Regression. 2nd Edition, John Wiley, New Jersey. 2008 2) Kleinbaum DG & Klein M. Logistic Regression: A Self-Learning Rex. 2nd edition, Springer, NewYork, 2002 3) Dupont WD. Statistical Modeling for Biomedical Researchers: A simple introduction to the analysis of complex data. 2nd Edition. Cambridge University Press. 2009. Available online in the U of A Library: http://site.ebrary.com/lib/ualberta/detail.action?docID=10277518 Proportional hazards regression 1) Hosmer DW and Lemeshow S. Applied Survival Analysis. 2nd [SPH 619, Biostatistics II] 2016 Course Syllabus

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Edition. Wiley. New York. 2008. 2) Kleinbaum DG & Klein M. Survival analysis [electronic resource]: a self-learning text. 2nd edition, Springer, NewYork, 2005 3) Dupont WD. Statistical Modeling for Biomedical Researchers: A simple introduction to the analysis of complex data. 2nd Edition. Cambridge University Press. 2009. Available online in the U of A Library: http://site.ebrary.com/lib/ualberta/detail.action?docID=10277518

Course Evaluation Mid Point Evaluation:

Final Course Evaluation:

As is the case with all SPH instructors, I am interested in improving the course. I need to hear from you in order to do that well. I will gather feedback and recommendations from you at the mid-point of the course, by asking a student to administer and deliver an anonymous course evaluation back to the instructor(s).

Following completion of the course, you will receive a standardized summative evaluation. The standard University of Alberta course evaluation procedure will be followed. This will involve a standard questionnaire with anonymous responses returned to the Student Services Coordinator.

Student Evaluation Assignment Percentage Take home assignments (5)

30%

Mid-term examination

30%

Final examination

40%

Date See the schedule on page 8 10:30 AM to 12:30 AM, February 25, 2015 9:00 AM to 12:00 noon, April 14, 2015

Grading University of Alberta Calendar Section 23.4 Regulations and Information for Students Evaluation Procedures and Grading System The University of Alberta Grading System The University of Alberta uses a letter grading system with a four-point scale of numerical equivalents for calculating grade point averages. [SPH 619, Biostatistics II] 2016 Course Syllabus

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Grades reflect judgments of student achievement made by instructors. These judgments are based on a combination of absolute achievement and relative performance in a class. Some instructors assign grades as intervals during the course and others assign marks (e.g. percentages) throughout the term and then assign a letter grade at the end. Instructors must adapt their approaches to reflect the letter grading system. Grade distribution should reflect those shown in this document. (EXEC 03 FEB 2003)

Grading in Graduate Courses Letter Grade Grade A+ A AB+ B BC+ C CD+ D F

Descriptor Excellent

Good Satisfactory Failure

Academic Integrity

Point Value 4.0 4.0 3.7 3.3 3.0 2.7 2.3 2.0 1.7 1.3 1.0 0.0

Plagiarism is a serious offence. The University of Alberta is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect. Students are particularly urged to familiarize themselves with the provisions of the Code of Student Behaviour (online at www.ualberta.ca/CodeofStudentBehaviour) and avoid any behaviour which could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts and/or participation in an offence. Academic dishonesty is a serious offence and can result in suspension or expulsion from the University. University of Alberta policy about course outline can be found in Section 23.4(2) of the University Calendar. (GFC 29 SEP 2003)

[SPH 619, Biostatistics II] 2016 Course Syllabus

University of Alberta, School of Public Health Page 5

Schedule at a Glance Date January 5 January 7 January 12 January 14 January 19 January 21 January 26 January 28 February 2 February 4 February 9 February 11 February 16 February 18 February 23 February 25 March 1 March 3 March 8 March 10 March 15 March 17 March 22 March 24 March 29 March 31 April 5 April 7 April 14

Topic Introduction to multiple linear regression analysis Estimation & hypothesis testing Hypothesis testing Regression and ANOVA Confounding and interaction Assessment of collinearity/ Model building Model building Regression diagnostics Analysis of covariance (ANCOVA) Analysis of covariance (ANCOVA) Introduction to logistic regression Interpretation of continuous independent variables Interpretation of categorical independent variables Reading Week (No class) Reading Week (No class) Hypothesis testing Midterm examination (9:00 AM to 11:00 AM) Hypothesis testing Interaction and confounding Model building Diagnostics/ conditional logistic regression Introduction to proportional hazards regression Hazard ratios Hypothesis testing Adjusted survival curves Testing proportional hazards assumption Non-proportional hazards model Time-dependent variables Review Final Examination (9:00 AM to 12:00 Noon)

Instructor Sentil Sentil Sentil Sentil Sentil Sentil Sentil Sentil Sentil Sentil Gian Gian

Assignment

Assignment 1

Assignment 2

Practice questions

Gian Sentil Gian Gian Gian Sentil Sentil Sentil Sentil Sentil Sentil Sentil Sentil Sentil

Assignment 3

Assignment 4

Assignment 5 Practice questions

Office hours: Mondays & Wednesdays from 11:50 AM to 12:30 PM in the classroom. If you like to see me in the office, please send me an e-mail to arrange a time for the meeting

[SPH 619, Biostatistics II] 2016 Course Syllabus

University of Alberta, School of Public Health Page 6