Our team of PhD data science specialists serves the Harvard social science community. We perform free in-person consulting on publication research issues as a part of the Institute for Quantitative Social Science. Our services are available to faculty, postdocs, graduate students, staff, and undergraduates writing a senior thesis. Specifically, we aim to provide advice on:

  • Data analysis and programming
  • Organization, secure storage, and sharing of data
  • Research project planning
  • Training in the use of both established software packages and emerging tools

To schedule a consultation or request help, please send a detailed description of your specific research problem, your affiliation (School / Dept.), and position (e.g., grad student) to help@iq.harvard.edu or use our contact form.

Our team also offers additional data science services. If you have a data science problem and you wish to speak to us, please contact us at help@iq.harvard.edu.

My Data Science Tool Box

This post describes the tools I currently use for working with data. People often ask me to recommend specific tools, and I always hesitate, because so much boils down to personal preference. I recently added a workshop to the DSS lineup providing an overview of popular tools for working with data. The core idea is that researchers have a lot of choices available when it comes to choosing tools to implement a reproducible workflow. For example, it doesn't really...

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Update: Stata v14.1 and 15 Advisory: xtreg, fe does what you expect; manual is incorrect

UPDATE: Sunday, March 4

Yesterday, I received the following message from David Drukker, the Executive Director of Econometrics at Stata:

"The xtreg-fe command in Stata produces consistent point estimates and
standard errors for all the model parameters.  There is a typo on page 27 of
https://www.stata.com/manuals/xtxtreg.pdf .  The formula for bar(bar(y))
should be the grand mean instead of the average of the panel-level means.

William Gould explicitly derived the grand mean as the term to add back in

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