PSTAT 175: Final Project Due December 4, 2020
The intention is that each group will find some survival analysis data to analyze. Find data that is
interesting to you, and that poses some relevant inference questions.
A good data set will generally have at least 200 subjects that are observed with some censoring.
Each subject will also have at least three covariates (columns in your data frame other than time
and status) that can be used in the model.
Requirements
All the projects will be different because your report will depend on the type of data that you have
to analyze. Here is a list of minimal requirements for all projects.
1. Describe the data set and the aim of modeling (e.g. estimation, modeling, testing.) Include
the key scientific question that motivated the data collection.
2. Plot the data. Provide at least 3 graphs that are clearly labeled and are appropriate to your
goals of inference.
3. Estimate coefficients for the appropriate models and perform diagnostic checks. Provide ap-
propriate confidence intervals.
4. Tackle at least one aspect of the data that is different from what we have already done in
the labs or assignments. This may be trying out a generalization of a model, or exploring an
alternative way of doing the inference.
5. Please acknowledge the source of your data in the project.
Your project report should be self-contained, and you should clearly describe using words and clearly
annotated plots what techniques you used and why you thought they were necessary. You may
include R output but it should be described fully in the text of the report. Please provide careful
citations of both the sources of your data, and other references that you consulted.
If you are looking for data, some possible data sets will be posted on GauchoSpace, but feel free
to look for your own data.

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