Event History Analysis for the Social Sciences, CS&SS 544
Winter 2022
Email: djholman@u.washington.edu
Voice: 206-543-7586
Fax: 206-543-3285
Office: Padelford C-019 (CSSS)
Note: The first week of this course is being held on-line via Zoom. Registered students have received an email with the meeting information. Access to handouts, course notes, etc. require a UWNetID login. If you cannot access these items, contact the instructor.
Media (Recorded Lectures)
Any recorded lectures and lecture links are available here.
Scope
Scope: Event history analysis is an important analytical tool in many fields of the social sciences. This course covers the standard tools used for event history analysis--things like parametric survival models, life tables, Kaplan Meier estimates, and the Cox proportional hazards model. Additionally, the course focuses on building a tool kit so that you can develop custom event history models that involve non-standard methods like subgroup heterogeneity, modeling a non-susceptible subpopulation, mixture models, models for clustered observations, multi-state models and social diffusion models. This course is not specific to any field within the social sciences, but many of the examples are taken from population studies.
Objectives: After completing this course you will have (1) a working familiarity with the concepts and tools for solving quantitative problems in the statistical analysis of time to events; (2) developed the skills and background to evaluate the use (and misuse) of event history analysis in contemporary social science research; (3) built a tool kit for developing custom event history models.
Times
Tuesday and Thursday at 10:30 am-12:20 pm in Savery Hall (SAV) 136.
Office hours: I will typically be available after class for office hours on Thursdays. I will hold Zoom office hours from 4 to 4:50 pm on Tuesdays here. Other times can be arranged. Call (3-7586 or 3-8110) or email (djholman@u.washington.edu) me with questions or to set up an appointment.
Readings
The textbooks are
- Singer JD, Willett JB (2003) Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford: Oxford University Press.
- Box-Steffensmeier JM, Jones BS (2004) Event History Modeling: A Guide for Social Scientists. Cambridge: Cambridge University Press.
Additional readings (here) and handouts (here) will supplement the text. These readings will illustrate principles discussed in lecture and the text, and will also be used as the basis for some class discussions.
A selection of readings (largely collected by past students of this course) are available here
Grading
Grades: There will be 5 problem sets (12% each) that will make up 60% of your final grade, and a final research poster (40%). There are no exams.
Problem sets
Problem sets: The five problem sets will consist of analytical exercises and other short problems. Frequently, the problems will require the use of computer software.
I recommend that you get an account on the CSDE Windows network. The CSDE systems have many useful programs for doing event history analysis (request a Windows account here). Data sets for this course will be available on both the course web site and the CSDE server.
You can use books, readings, notes, and web pages to help you work on the problems. In fact, you can work in groups on most exercises. Grades for late problem sets are reduced by 10% per day, including any fraction of a day late.
Software
You can use any software that works for you and gets the job done. For example, when we work with the Cox proportional hazards regression model, almost any standard statistical software will work. For other assignments only a few "packages" will be able to easily perform the analysis. I strongly encourage you to do most of your work in a statistical programming language like R, Matlab, or Gauss. Most of the coding examples in this class will be in R, so it will be easiest for you to work in R unless you have excellent skills in another language. If there is sufficient interest, I will offer optional weekly computer lab sessions to help you work on course material using the R programming language. Short courses introducing R are given by CSSCR during the first two weeks of the quarter.
Project
40% of your course grade will be based on a project in the form of a completed paper or poster with original research, analysis, and presentation using the methods covered in this course. A one paragraph description of your project will be due during week 5. If you don't already have a data set in mind, start early locating one. CSSCR has a data consultant who can help identify and procure relevant data sets.
Course Policies
Academic misconduct
The university's policy on plagiarism and academic misconduct is a part of the Student Conduct Code, which cites the definition of academic misconduct in the WAC 478-121. According to this section of the WAC, academic misconduct includes: "Cheating"-such as "unauthorized assistance in taking quizzes", "Falsification" "which is the intentional use or submission of falsified data, records, or other information including, but not limited to, records of internship or practicum experiences or attendance at any required event(s), or scholarly research"; and "Plagiarism" which includes "[t]he use, by paraphrase or direct quotation, of the published or unpublished work of another person without full and clear acknowledgment."
The UW Libraries have a useful guide for students here.
Accommodation
Your experience in this class is important to me. If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to me at your earliest convenience so we can discuss your needs in this course. The website for the DRO provides other resources for students and faculty for making accommodations.
Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW's policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.
Inclusion
Among the core values of the university are inclusivity and diversity, regardless of race, gender, income, ability, beliefs, and other ways that people distinguish themselves and others. If any assignments and activities are not accessible to you, please contact me so we can make arrangements to include you by making an alternative assignment available.
Learning often involves the exchange of ideas. To include everyone in the learning process, we expect you will demonstrate respect, politeness, reasonableness, and willingness to listen to others at all times-even when passions run high. Behaviors must support learning, understanding, and scholarship.
Preventing violence is a shared responsibility in which everyone at the UW plays apart. If you experience harassment during your studies, please report it to the SafeCampus website (anonymous reports are possible). SafeCampus provides information on counseling and safety resources, University policies, and violence reporting requirements help us maintain a safe personal, work and learning environment.
Safety
You must wear a suitable face covering at all times in the classroom. If you are ill, please do not come to class (or the campus, for that matter). More information about COVID-19 safety and policy can be found here.
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Readings:
- Box-Steffensmeier and Jones Ch 1, 2
- Singer and Willett Ch 9
- Lecture 1 Notes
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Readings:
- Box-Steffensmeier and Jones Ch 3
- Review probability theory, distributions and random variables, and likelihood as needed: here
- Distributions Handout
- Likelihood Handout
- Overheads (Jan 11)
- Overheads (Jan 13)
- Note: Class will continue to meet on-line through December
- Problem set 1 distributed (Thursday)
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Readings:
- Box-Steffensmeier and Jones Ch 3
- Messy Data Handout
- Covariates Handout
- Overheads (Jan 18)
- Overheads (Jan 20)
- Problem set 1 due (Thursday)
- Problem set 2 distributed (Thursday)
- Problem set 2 Data set
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Readings:
- Gehan (1969)
- Blossfeld and Rohwer Ch 3
- Singer and Willett Ch 10, 13
- Overheads (Jan 25)
- Overheads (Jan 27)
- Problem set 2 due (Thursday)
- Problem set 3 distributed (Thursday)
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Readings:
- Box-Steffensmeier and Jones Ch 4
- Singer and Willett Ch 14
- Notes on Writing an Event History Analysis Paper (Tuma)
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Readings:
- Box-Steffensmeier and Jones Ch 4
- Singer and Willett Ch 15
- Overheads (Feb 8)
- Overheads (Feb 10)
- Problem set 3 due (Tuesday).
- One paragraph project description due (Thursday)
- Problem set 4 distributed (Thursday)
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Readings:
- Box-Steffensmeier and Jones Ch 6, 8
- Singer and Willett Ch 11, 12
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Readings:
Materials:
- Overheads (Feb 22)
- Overheads (Feb 24)
- Problem set 4 due (Tuesday)
- Problem set 5 distributed (Tuesday)
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Readings:
- Box-Steffensmeier and Jones Ch 9
- Vaupel and Yashin (1985).
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Readings:
- Box-Steffensmeier and Jones Ch 10
- Wood et al. (1994);
- Strang and Tuma (1993)