Survival Analysis
QAC 314
Spring 2016
| Section:
01
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| Certificates: Applied Data Science |
Survival or Event History Analysis focuses on modeling and analysis of time-to-event data--e.g. onset of a disease, duration of a strike, failure of a biological, a physical or a social system, recidivism, etc. The course introduces students to survival and hazard functions, the analysis of censored data using parametric and non-parametric estimation methods and compares survival curves for different groups and discussed competing risk models. The emphasis is on the applications of the different methods with the objective of broadening computational skills in R and/or SAS, and to reinforce statistical writing and communication. These skills will be applied to a variety of problems in political science, public health, engineering, and medicine. |
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| Credit: .5 |
Gen Ed Area Dept:
NSM QAC, SBS QAC |
| Course Format: Laboratory Course | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: [QAC201 or SOC257 or GOVT201 or PSYC280 or NS&B280] OR [QAC380 or PSYC395] OR ECON300 OR [GOVT367 or QAC302] OR PSYC200 |
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Fulfills a Requirement for: (CADS)(DATA-MN)(HRAD-MN)(PSYC) |
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Past Enrollment Probability: Not Available |
| SECTION 01 - 3rd Quarter | | Special Attributes: CQC |
Major Readings: Wesleyan RJ Julia Bookstore
Allison, Paul D., SURVIVAL ANALYSIS USING SAS, SAS Publishing, 2012
Kleinbaum, David G. and Klein, Mitchel, SURVIVAL ANALYSIS: A SELF-LEARNED TEXT, Springer, 2012 (Available electronically through Wesleyan libraries)
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Examinations and Assignments:
Several homework assignments and a take-home final exam linked to the course project. Part of the grade will depend on class preparation and participation. |
Additional Requirements and/or Comments:
An introductory statistics/data analysis background is a prerequisite for the course and that is why QAC201, or 380, or GOVT367 etc. are listed as formal prerequisites. Pre-req overrides will be approved by the Professor for students who satisfy this basic requirements through other course work. The course includes a strong lab component and programming with a statistical analysis software (e.g. SAS, or Stata, or R) is a significant part of the course work. |
| Instructor(s): Nazzaro,Valerie L. Times: ..T.R.. 10:30AM-11:50AM; Location: ALLB107; |
| Total Enrollment Limit: 16 | | SR major: 0 | JR major: 0 | | |
| Seats Available: 10 | GRAD: 1 | SR non-major: 6 | JR non-major: 6 | SO: 3 | FR: 0 |
| Web Resources: Syllabus |
| Drop/Add Enrollment Requests | | | | | |
| Total Submitted Requests: 1 | 1st Ranked: 0 | 2nd Ranked: 0 | 3rd Ranked: 0 | 4th Ranked: 0 | Unranked: 1 |
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