Talks

An overview of basic research design patterns in causal inference, modern extensions, and data management strategies to set up a causal inference initiative for success

An introduction to inverse propensity of treatment weighting for program evaluation with applications to Two Million Texans’ relational organizing campaign during the 2022 midterms

An argument for the individual and organization-wiide benefits of teaching new developers Shiny with a modules-first paradigm

Interrogating the data generating process to devise better data quality tests.

An exploration of how data producers and consumers can use column names as interfaces, configuations, and code to improve data quality and discoverability. The second half of the talk demonstrates how to implement these ideas with my dbtplyr dbt package.

Exploring the benefits of using controlled vocabularies to encode metadata in column names, and demonstrations of implementing this approach with the convo R package or dbt extensions of SQL.

An overview of the unique design challenges and opportunities when building R packages for use inside of a single organization versus open-source. By using the jobs-to-be-done framework, this talk explores how internal packages can be better teammates by following specific design patterns for API design, testing, documentaiton, and more.

A lightning talk on key features of the projmgr package

How and why to refactor one time analyses in RMarkdown into sustainable data products

An overview of how the tidycf R package led to process and cultural change at Capital One

A variety of related talks to creating innersource culture with R packages and related tools