R-statistics blog

Managing a statistical analysis project – guidelines and best practices

In the past two years, a growing community of R users (and statisticians in general) have been participating in two major Question-and-Answer websites:

  1. The R tag page on Stackoverflow, and
  2. Stat over flow (which will soon move to a new domain, no worries, I’ll write about it once it happens)

In that time, several long (and fascinating) discussion threads where started, reflecting on tips and best practices for managing a statistical analysis project.  They are:

On the last thread in the list, the user chl, has started with trying to compile all the tips and suggestions together.  And with his permission, I am now republishing it here.  I encourage you to contribute from your own experience (either in the comments, or by answering to any of the threads I’ve linked to)

From here on is what “chl” wrote:

These guidelines where compiled from SO (as suggested by @Shane), Biostar (hereafter, BS), and SE. I tried my best to acknowledge ownership for each item, and to select first or highly upvoted answer. I also added things of my own, and flagged items that are specific to the [R] environment.

Data management

Coding

Analysis

Versioning

Editing/Reporting

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