ST 495 Survival Analysis
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1 1 of 7 2/21/2014 1:48 PM ST 495 Survival Analysis Section TBD SPRING Credit Hours Special Notes The course is graded pass/fail with the threshold for pass being 70% of the total possible points. Course Description This is a Special Topics in Statistics course. Learning Outcomes Introduce parametric, semi-parametric, and non-parametric methods for estimation and inference with survival data. To develop intuition and build connections with standard tools from mathematical statistics, the first part of the course will focus on likelihood-based estimation and inference. We will then extend to non- and semi-parametric models. Lectures will be a mix of mathematical derivations, worked examples, and R code. We will cover a substantial amount of material in a relatively short amount of time so PLEASE ask questions as they arise to avoid getting behind. Throughout the course, we will be doing a number of short active learning activities where you will be asked to work through a short calculation, thought experiment, or `teachyour-neighbor' exercise. These are a great way to solidify your understanding, help your classmates, and most importantly breakup the monotony of my droning lecture! Course Structure Work together, work together, work together. To goal of this course is for you to understand and be able to apply the material. You are encouraged to do you homework in groups, share ideas, code, and homework solutions. Obviously copying a classmates solution directly is discouraged and will likely not provide good preparation for the quizzes and exams! Instructors Dr Eric Benjamin Laber (eblaber) - Instructor eric_laber@ncsu.edu Web Page: Phone: (919) Office Location: 5216 SAS Hall Office Hours: 1:00-2PM Tuesdays Course Meetings
2 2 of 7 2/21/2014 1:48 PM Lecture Days: T Time: 3:00 PM - 4:15 PM Campus: Main Location: 1216 SAS Hall This meeting is required. Meeting Notes There will be two (probably more later on) extra review sections lead by the TA Kasturi Talapatra. The first will cover R and is on Thursday Jan 9, from 4:30-5:30 in the first floor computer lab. The second will be on Jan 16, from 4:30-5:30 in the first floor computer lab and will cover maximum likelihood theory. Course Materials Textbooks Statistical Models and Methods for Lifetime Data - Jerald F. Lawless Edition: 2nd Edition ISBN: Cost: Varies This textbook is required. Expenses Materials Requisites and Restrictions Prerequisites Co-requisites Restrictions General Education Program (GEP) Information GEP Category This course does not fulfill a General Education Program category. GEP Co-requisites This course does not fulfill a General Education Program co-requisite. Transportation This course will not require students to provide their own transportation. Non-scheduled class time for field
3 3 of 7 2/21/2014 1:48 PM trips or out-of-class activities is NOT required for this class. Safety & Risk Assumptions Grading Grade Components Component Weight Details Homework 40% There will be roughly eight homework assignments these contribute to 40% of the total possible points. Quizzes 20% Four quizzes will contribute 20% to the total possible points. Midterms 20% Two midterms will contribute 20% the total possible points. Final Group Project 10% A final group project will contribute the final 10%. Letter Grades This Course uses Standard NCSU Letter Grading: 97 A A < A- < B+ < B < B- < C+ < C < C- < D+ < D < D- < 63 0 F < 60 Requirements for Credit-Only (S/U) Grading In order to receive a grade of S, students are required to take all exams and quizzes, complete all assignments, and earn a grade of C- or better. Conversion from letter grading to credit only (S/U) grading is subject to university deadlines. Refer to the Registration and Records calendar for deadlines related to grading. For more details refer to Requirements for Auditors (AU) Information about and requirements for auditing a course can be found at /regulation/reg Policies on Incomplete Grades
4 4 of 7 2/21/2014 1:48 PM If an extended deadline is not authorized by the instructor or department, an unfinished incomplete grade will automatically change to an F after either (a) the end of the next regular semester in which the student is enrolled (not including summer sessions), or (b) the end of 12 months if the student is not enrolled, whichever is shorter. Incompletes that change to F will count as an attempted course on transcripts. The burden of fulfilling an incomplete grade is the responsibility of the student. The university policy on incomplete grades is located at Late Assignments Attendance Policy For complete attendance and excused absence policies, please see /regulation/reg Attendance Policy Absences Policy Makeup Work Policy Additional Excuses Policy Academic Integrity Academic Integrity Students are required to comply with the university policy on academic integrity found in the Code of Student Conduct found at Academic Honesty See for a detailed explanation of academic honesty. Honor Pledge Your signature on any test or assignment indicates "I have neither given nor received unauthorized aid on this test or assignment." Electronically-Hosted Course Components There are no electronically-hosted components for this course. Accommodations for Disabilities Reasonable accommodations will be made for students with verifiable disabilities. In order to take advantage of available accommodations, student must register with the Disability Services Office ( For more information on NC State's policy on working with students with disabilities, please see the Academic Accommodations for Students with Disabilities Regulation at Non-Discrimination Policy NC State University provides equality of opportunity in education and employment for all students and employees. Accordingly, NC State affirms its commitment to maintain a work environment for all employees
5 5 of 7 2/21/2014 1:48 PM and an academic environment for all students that is free from all forms of discrimination. Discrimination based on race, color, religion, creed, sex, national origin, age, disability, veteran status, or sexual orientation is a violation of state and federal law and/or NC State University policy and will not be tolerated. Harassment of any person (either in the form of quid pro quo or creation of a hostile environment) based on race, color, religion, creed, sex, national origin, age, disability, veteran status, or sexual orientation also is a violation of state and federal law and/or NC State University policy and will not be tolerated. Retaliation against any person who complains about discrimination is also prohibited. NC State's policies and regulations covering discrimination, harassment, and retaliation may be accessed at or Any person who feels that he or she has been the subject of prohibited discrimination, harassment, or retaliation should contact the Office for Equal Opportunity (OEO) at Course Schedule NOTE: The course schedule is subject to change. Lecture T 3:00 PM - 4:15 PM Intro TBD - TBD Lecture T 3:00 PM - 4:15 PM Using R TBD - TBD Computer Lab/Homework: Lecture T 3:00 PM - 4:15 PM Parametric models TBD - TBD Lecture T 3:00 PM - 4:15 PM Review MLE TBD - TBD Homework: Lecture T 3:00 PM - 4:15 PM Censoring and LH TBD - TBD Homework: Lecture T 3:00 PM - 4:15 PM More censoring and LH TBD - TBD 2.3, 2.4 Lecture T 3:00 PM - 4:15 PM Nonparametric methods TBD - TBD 3.1, Lecture T 3:00 PM - 4:15 PM More nonpar methods TBD - TBD
6 6 of 7 2/21/2014 1:48 PM 3.2.2, Lecture T 3:00 PM - 4:15 PM Nonpar and graphics TBD - TBD 3.2.4, 3.3.1, Lecture T 3:00 PM - 4:15 PM Trunc and interval censoring TBD - TBD 3.5.1, 3.5.2, Lecture T 3:00 PM - 4:15 PM Review/catch-up TBD - TBD Lecture T 3:00 PM - 4:15 PM Midterm I TBD - TBD Lecture T 3:00 PM - 4:15 PM Inference par. models TBD - TBD 4.1 Lecture T 3:00 PM - 4:15 PM More inf. for par. models TBD - TBD 4.2, 4.3, 4.6 Lecture T 3:00 PM - 4:15 PM Location scale models TBD - TBD 5.1, 5.2 Lecture T 3:00 PM - 4:15 PM More location scale models TBD - TBD 5.3, 5.4 Lecture T 3:00 PM - 4:15 PM Par reg models TBD - TBD 6.3 Lecture T 3:00 PM - 4:15 PM More par reg models TBD - TBD 6.4, 6.5 Lecture T 3:00 PM - 4:15 PM Review/catch-up TBD - TBD Lecture T 3:00 PM - 4:15 PM Midterm II TBD - TBD Lecture T 3:00 PM - 4:15 PM Semi-parametric models TBD - TBD 7.1, 7.1.2, Lecture T 3:00 PM - 4:15 PM More semi-parametric models TBD - TBD 7.2 Lecture T 3:00 PM - 4:15 PM Even more semi-parametric models TBD - TBD 7.3
7 7 of 7 2/21/2014 1:48 PM Lecture T 3:00 PM - 4:15 PM Enough with the semi-parametric models already! TBD - TBD 7.4
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