Survival Analysis (Special Blog Entry)

Today I'm giving a guest lecture on survival analysis (also known as event history analysis) in my colleague Dr. Du Feng's graduate class on developmental (longitudinal) data analysis. Survival analysis is not a topic for introductory statistics, but this blog seemed to be as good a place as any for putting these web links to supplement my presentation.

Survival analysis is appropriate when a researcher has a dichotomous outcome variable that can be monitored at regular time intervals to see if each participant has switched from one status to another (e.g., in medical research, from alive to dead).

Here are a couple of documents I found on the web. First is a brief one from University College London that presents both a survival curve and a hazard curve, concepts that we shall discuss during class. Second is a more elaborate document from the University of Minnesota that discusses additional issues, including "censored" data.

The focus of my talk will be a class project from when I taught graduate research methods in the spring of 1998. The study led to a poster paper at the 1999 American Psychological Association conference (copies available upon request). We took advantage of the fact that People magazine, which comes out weekly and is archived in the Texas Tech library, lists celebrity marriages and divorces (and other developments) in a "Passages" section (here's an example, from after the study was completed).

We were looking at the survival of celebrity marriages until divorce. What makes the study a little unusual is that two events had to occur for a couple to provide complete data: the couple would have to get married, then get divorced. Quoting from our paper:

All issues of People between January 1, 1990 and June 30, 1997 were examined, for a total of 392 weeks. All marriages and divorces during this period were recorded, but only those couples whose marriages took place during the study period were used. To facilitate the survival analysis, for each couple the week number of the marriage and of the divorce (if any) were recorded...

Regarding the week numbers noted above, the issue of People dated January 1, 1990 represented week number 1, the January 8, 1990 issue represented week number 2, and so forth, up through the June 30, 1997 issue, which represented week number 392.

The particular type of survival analysis we conducted is called Cox Regression. Like other kinds of regression techniques, Cox Regression tests the relationship of predictor variables (covariates) to an outcome, in this case the hazard curve.

I hope you find this information useful and that everyone "survives" the lecture. For a nice, though somewhat dated, overview of the technique, I would recommend the following article:

Luke, D.A. (1993). Charting the process of change: A primer on survival analysis. American Journal of Community Psychology, 21, 203-246.