College of Public Health

UNIVERSITY OF KENTUCKY COLLEGE OF PUBLIC HEALTH

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Course Syllabus

CPH 630 / STA 681 Biostatistics II Spring 2014 ______

Course meeting schedule

Lectures will take place on Tuesdays from 3:30 to 5:30 p.m. in (Charles T Wethington) CTW 0405. Labs will take place on Thursdays at the Multi-Disciplinary Science Building (MDS) 221. For Section 001, lab will take place from 4:00-6:00pm. For Section 002, lab will take place from 6:00-8:00pm.

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Contact information

Instructor: Dr. Philip Westgate Multi-Disciplinary Science Building (MDS), Room 205B.

Telephone: (859) 218-2082

E-mail: [email protected] (Preferred Contact)

Office Hours: To be determined

Course Assistant: Josh Lambert ([email protected]) Multi-Disciplinary Science Building (MDS), Room 205C

Office Hours: Wednesdays 2pm-3pm.

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Course description

CPH 630 / STA 681 covers statistical methods used in public health studies. This includes receiver operator curves, multiple regression, logistic regression, confounding and stratification, the Mantel-Haenszel procedure, and the Cox proportional hazards model.

Course rationale:

To learn the basics of a variety of popular statistical modeling approaches utilized in public health studies. Students will be able to apply these approaches in their future roles in public health, and will be able to understand the role of biostatistics.

Course prerequisites

STA 580 or equivalent Course objectives

Students completing CPH 630 / STA 681 will be able to: 1. Use and understand Multiple Linear Regression, logistic regression, poisson regression, and cox proportional hazards regression to solve biostatistical problems in a wide array of different possible public health areas. 2. Use and understand SAS, a popular statistical software. 3. Understand the role of biostatistics in public health studies, and understand assumptions behind statistical methodologies. 4. Write statistical reports.

Competency Attainment

Please see the end of the syllabus.

Student learning outcomes:

Upon successful completion of this course, a student will be able to identify appropriate statistical methods for his or her research and be prepared to critically review the statistical methods incorporated in public health literature. Specifically, the objectives of the course are as follows: 1. Learn basic principles of probability for binomial and Poisson distributions. 2. Utilize statistical methodologies such as multiple regression, logistic regression, Poisson regression, and the Cox proportional hazards model. 3. Learn basic principles for designing and analyzing epidemiologic studies, including confounding, standardization, and stratification. 4. Develop a familiarity with the design and analysis of studies routinely used in public health and medicine: crossover studies, equivalence studies, meta-analysis studies, and studies with clustered responses.

Textbooks

Bush (2012). Biostatistics: An Applied Introduction for the Public Health Practitioner, First Edition. Delmar, Cengage Learning. (Highly Recommended)

Rosner (2011). Fundamentals of Biostatistics, Seventh Edition. Brooks/Cole, Cengage Learning. (Optional) Course requirements and learner evaluation

Course grades will be based upon evaluation of the following activities:

Readings (15%): Students will be asked to answer a series of questions pertaining to published articles that utilize the methods discussed in lecture and lab. There will be a total of three such readings worth 5% each.

Homeworks (30%) Students will be expected to complete three homework assignments worth 10% each.

Statistical Methods Application Group Projects (25%) Students will be expected to complete two group projects (Project 1 is worth 10%, Project 2 is worth 15%) in biostatistics applications. In these projects, students will be expected to provide written reports on the analysis and interpretation of data.

Quizzes (15%) Five short quizzes (worth 3% each) will be given throughout the semester. If you are unable to attend lecture on the day a quiz is given, it is your responsibility to contact Dr. Westgate and schedule a time to take the quiz prior to the lecture in which the quiz is given. Quizzes will be given promptly at the beginning of lecture and will last for a minimum of 10 minutes. It is your responsibility to show up to lecture on time in order to ensure you have the full allotted time to take each quiz.

Final Exam (15%) The final exam will assess your knowledge of the basic statistical methods presented in this course.

Grading Scale: 100 – 90 = A 89 – 80 = B 79 – 60 = C 60 – 0 = E

Submission of Assignments: All assignments are to be submitted on Canvas (https://canvas.instructure.com/login) by the assigned due date.

Instructor expectations

1. I expect you to attend every class session. The components are highly interrelated; missing a class will detract from the learning potential of subsequent sessions. 2. I expect you to be in the classroom and prepared to begin work at the scheduled starting time for each session. 3. I expect you to actively participate in the discussions. 4. I expect you to submit papers using proper English grammar, syntax, and spelling. You are encouraged to use spell check and grammar check prior to submitting your written work. The Writing Laboratory is available to anyone who may need assistance. Academic honesty Academic honesty is highly valued at the University. You must always submit work that represents your original words or ideas. If any words or ideas used in a class assignment submission do not represent your original words or ideas, you must cite all relevant sources and make clear the extent to which such sources were used. Words or ideas that require citation include, but are not limited to, all hard copy or electronic publications, whether copyrighted or not, and all verbal or visual communication when the content of such communication clearly originates from an identifiable sources. Per university policy, students shall not plagiarize, cheat, or falsify or misuse academic records. Students are expected to adhere to University policy on cheating and plagiarism in all courses. The minimum penalty for a first offense is a zero on the assignment on which the offense occurred. If the offense is considered severe or the student has other academic offenses on their record, more serious penalties, up to suspension from the university, may be imposed. All incidents of cheating and plagiarism are taken very seriously at the University of Kentucky, and there are specific policies and procedures in place to prosecute them. See S.R. 6.3.0 (PDF) for the exact Senate Rules regarding academic offenses.

Accommodations If you have a documented disability that requires academic accommodations, please see me as soon as possible during scheduled office hours. In order to receive accommodations in this course, submit to me a Letter of Accommodation from the Disability Resource Center. If you have not already done so, please register with the Disability Resource Center for coordination of campus disability services available to students with disabilities. Contact Jake Karnes via email at [email protected] or by telephone 859-257-2754. You may also visit the DRC website for information on how to register for services as a student with a disability: http://www.uky.edu/StudentAffairs/DisabilityResourceCenter/

Religious Observances Students will be given the opportunity to make up work (typically, exams or assignments) when students notify their instructor that religious observances prevent the student from completing assignments according to deadlines stated in this syllabus. Students must notify the course instructor at least two weeks prior to such an absence and propose how to make up the missed academic work.

Late work policy Only students with university or instructor excused absences will be allowed to submit late work without penalty. Late work is defined as any work handed in after the scheduled due date and time. It is the student’s responsibility to make arrangements for determining and handing in missed work, preferably in advance, but no later than one week after the absence. In all other cases, late work will be penalized 15% for each day late, and assignments will not be accepted more than one week late.

Attendance Policy The course is designed so that students should be successful with active participation and regular, punctual attendance. It is understandable that students may miss class; however, it is the student’s responsibility to determine what assignments were missed and what material was covered. Students missing 5 or more class periods (excused or unexcused) will receive an E for the course.

Inclement weather The University of Kentucky has a detailed policy for decisions to close in inclement weather. This policy is described in detail at http://www.uky.edu/PR/News/severe_weather.htm or you can call (859) 257-1754. Course schedule and topics

Tentative Schedule of Topics and Assignments: Date Topic Readings Due Dates

BUSH: Chapters 1 & 2 Jan 21 Introduction to Terminology, Notation, and ROSNER: Chapters 2, 7, 8, & 12 ANOVA

Describing Data BUSH: Chapter 3 Jan 28 Simple and Multiple Linear Regression ROSNER: Chapter 11

Describing Data BUSH: Chapter 3 Feb 4 Simple and Multiple Linear Regression ROSNER: Chapter 11 Quiz 1

Describing Data BUSH: Chapter 3 Feb 11 Simple and Multiple Linear Regression ROSNER: Chapter 11 Linear Regression: BUSH: Chapter 3 Reading 1 Due Feb 18 Diagnostic Tests and Residuals ROSNER: Chapter 11 Multiple Linear Regression: BUSH: Chapter 3 Feb 25 Quiz 2 Confounding and Variable Selection ROSNER: Chapter 11

Categorical Methods: BUSH: Chapter 4 March 4 HW 1 Due Measures of Association ROSNER: Chapter 13

BUSH: Chapter 5 Quiz 3 March 11 Logistic Regression ROSNER: Chapter 13 Project 1 Due March 18 Spring Break

BUSH: Chapter 5 March 25 Logistic Regression Reading 2 Due ROSNER: Chapter 13 BUSH: Chapter 6 April 1 Count Data and Poisson Regression Quiz 4 ROSNER: Chapter 14 Survival Analysis: BUSH: Chapter 7 April 8 HW 2 Due Introduction and Mechanisms ROSNER: Chapter 14 Survival Analysis: BUSH: Chapter 7 Project 2 Due April 15 Log-Rank Test and Cox Regression ROSNER: Chapter 14

Survival Analysis: BUSH: Chapter 7 Quiz 5 April 22 Cox Regression ROSNER: Chapter 14 Reading 3 Due

April 29 Review for Final Exam HW 3 Due

Final Exam May 6 1pm General MPH and MPH Biostatistics Concentration Competencies that are at least partially met in this class:

General 1. Describe basic concepts of probability, random variation, and commonly used statistical probability distributions. 2. Recognize the assumptions and limitations of common statistical methods and choose appropriate approaches for analysis.

3. Use evidence based principles and scientific knowledge effectively when involved in evaluation and decision-making in public health.

Biostatistics Concentration 1. Apply the basic concepts of probability, random variation, and commonly used probability distributions. 2. Apply and interpret common univariate and multivariate statistical methods for inference. 3. Recognize the assumptions and limitations of common statistical methods and choose appropriate approaches for analysis. 4. Develop written and oral presentations based on statistical analyses for both public health professionals and educated lay audiences.