**Meeting location: 55 Washington St, Brooklyn, NY, Floor 8**|
Our speakers for the night will be Emily H Ho from Fordham & Samuel Crane from Amplify. Emily will be talking about working with psychological scales in R. Samuel will be talking about building a data dictionary using blogdown.
6:30-6:45 pm Introductions & Social
6:45-6:55 pm R-Ladies New York Announcements
6:55-7:25 pm Developing & Validating a Psychological Scale in R
7:25-7:55 pm Amplify, Blogdown & the Central Source of Truth
7:55-8:00 pm Community Announcements
8:00-8:30 pm Networking
Title: Developing & Validating a Psychological Scale in R
Abstract: If you've ever taken a personality quiz online or a career assessment at school (or that high-stakes college admissions test which shall not be named), you've come into contact with a validated scale. Using a recently developed scale as an example, I will walk through the process of how to create such a measure, from generating items to seeing the latent relationships between the items, testing for validity, & finally, how to ensure that the scale works 'in the wild'.
Bio: Emily H Ho is a behavioral scientist pursuing her PhD in psychometrics & quantitative psychology at Fordham. Her work develops & applies new methods to improve decision-making in areas like health, climate change, & intelligence analysis. She has previously worked at The College Board conducting analyses on test validity & reliability. Follow her on Twitter at @emilyhho.
Title: Amplify, Blogdown & the Central Source of Truth
Abstract: Having a central source of truth for all data descriptions is critical to the development of data literacy within an organization, but data dictionaries are tricky to maintain. This talk will discuss how I am solving this problem at Amplify by using R to develop a website with blogdown & then leveraging the Looker API & a custom metadata store to deliver comprehensive, accurate, & up-to-date information about our data.
Bio: Samuel is the Director of Data Science at Amplify, an educational technology company based in Brooklyn, NY. He leads a team of data scientists focusing on analytics, algorithm development, & measuring the impact of Amplifys curricula & assessments. Samuel is interested in statistical programming, reproducible research, data visualization, & the role of data in product development. Formerly a biologist & now a manager & data scientist, he loves to chat about building teams, the transition from academia to industry, beetles (his former obsession), & collecting wine.