Replication and Reproducibility in Social Sciences and Statistics: Overview and Practice

Lars Vilhuber
2019-10-01

Cornell University

Overview

  • High-level overview (60:00)
  • A very concrete example (remainder)

Replication and Reproducibility in Social Sciences and Statistics: Context, Concerns, and Concrete Measures

Paris presentation (alt)

DOI

Goals of this tutorial

  • Goal 1: Identify all the elements of a fully reproducible analysis
  • Goal 2: Be able to curate the data and code necessary for reproducible analysis
  • Goal 3: Robustness and automation - getting close to push-button reproducibility
  • Goal 4: Correctly document reproducible research

Requirements

Requirements

  • web browser
  • some R knowledge (not much)

Sub goals

  • show you enough of the toolkit to have you explore more
  • recognize (some) of the limitations
  • NOT make you a master of this today

Let's get started

Details: Goal 1: Elements of a fully reproducible analysis

Consider the AEA's suggested README and the Social Science Data Editors' guidance for verification: