Professor at the NYU Wagner Graduate School of Public Service
Professor at the NYU Center for Urban Science and Progress
NYU Provostial Fellow for Innovation Analytics
Julia Lane is a Professor at the NYU Wagner Graduate School of Public Service, at the NYU Center for Urban Science and Progress, and a NYU Provostial Fellow for Innovation Analytics. She cofounded the Coleridge Initiative, whose goal is to use data to transform the way governments access and use data for the social good through training programs, research projects and a secure data facility. The approach is attracting national attention, including the ...
If you are planning on conducting a systematic review consider using Covidence for your next project! Your UC Berkeley account gives you access to an unlimited number of reviews and citations per review, as well enhanced support.
As part of my Masters of Public Health Capstone Project, I completed a systematic review and meta-analysis to assess suicides among previously incarcerated persons. Covidence streamlined the most time-consuming and error-prone parts...
Openness, transparency, and reproducibility in research are critical to scientific progress. Yet, according to a 2016 internet-based survey of 1,576 researchers, 90% of respondents felt there was a slight or significant reproducibility crisis.1 Moreover, there are longstanding concerns that scientific journals favor positive or significant results—often referred to as publication bias—which may produce bodies of evidence that are incomplete or misleading (i.e., because studies which report null findings are not published).2 Publication bias can also arise when researchers choose...
Computational and data-driven research increasingly requires developing complex codebases. At the same time, many scientists don’t receive training in software engineering practices, resulting in, for some, the perception that scientists write terrible software. As scientists, good software should accelerate our work and facilitate its reproducibility. While building good coding practices takes some time and experience, it doesn’t require a...
Since becoming a Data Fellow at the D-Lab, I have had the opportunity to assist many talented social scientists through the D-Lab’s Consulting service. A regular consulting request is to help with the research design for a new project. These requests are understandable. For empirical researchers, a high-quality research design makes or breaks a research project. In this post, I suggest a few benefits of writing a skeleton design plan before writing any code whatsoever.
