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Rethinking literate programming in statistics

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  • E. F. Haghish

    (University of Freiburg)

Abstract

Literate programming is becoming increasingly trendy for data analysis because it allows the generation of dynamic-analysis reports for communicating data analysis and eliminates untraceable human errors in analysis reports. Traditionally, literate programming includes separate processes for compiling the code and preparing the documentation. While this workflow might be satisfactory for software documentation, it is not ideal for writing statistical analysis reports. Instead, these processes should run in parallel. In this article, I introduce the weaver package, which examines this idea by creating a new log system in HTML or LATEX that can be used simultaneously with the Stata log system. The new log system provides many features that the Stata log system lacks; for example, it can render mathematical notations, insert figures, create publication-ready dynamic tables, and style text, and it includes a built-in syntax highlighter. The weaver package also produces dynamic PDF documents by converting the HTML log to PDF or by typesetting the LATEX log and thus provides a real-time preview of the document without recompiling the code. I also discuss potential applications of the weaver package. Copyright 2016 by StataCorp LP.

Suggested Citation

  • E. F. Haghish, 2016. "Rethinking literate programming in statistics," Stata Journal, StataCorp LP, vol. 16(4), pages 938-963, December.
  • Handle: RePEc:tsj:stataj:v:16:y:2016:i:4:p:938-963
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    Cited by:

    1. Valérie Orozco & Christophe Bontemps & Elise Maigné & Virginie Piguet & Annie Hofstetter & Anne Lacroix & Fabrice Levert & Jean‐Marc Rousselle, 2020. "How To Make A Pie: Reproducible Research For Empirical Economics And Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 1134-1169, December.
    2. Valérie Orozco & Christophe Bontemps & Élise Maigné & Virginie Piguet & Annie Hofstetter & Anne Marie Lacroix & Fabrice Levert & Jean-Marc Rousselle, 2017. "How to make a pie? Reproducible Research for Empirical Economics & Econometrics," Post-Print hal-01939942, HAL.

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