Why and With Whom

This part asks why an analysis should be reproducible at all, and what an analyst owes to two groups of people: the collaborators who depend on the work and the participants whose records make it possible. It is the first part of the first quarter, and it is deliberately light on code; the chapters that follow supply the tools, and these supply the reasons for using them.

• 2  Why Reproducible Research distinguishes methods, results, and inferential reproducibility, and names the check that makes each common failure loud.
• 3  Team Science for Biostatisticians runs the intake conversation, places an engagement on the collaboration spectrum, and settles authorship.
• 4  De-identification and Data Ethics sets out the HIPAA de-identification pathways, what each costs the analysis, and the obligations that survive de-identification.

Each chapter opens with a short ‘Skip ahead?’ quiz. If the quiz at the start of a chapter is easy, skip to the next chapter; if it is not, the chapter is written for you.