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EVENT DETAILS |
Join us as we host the R-Ladies meetup!
In this event, we will be hosting a several great speakers & topics. Check out the agenda & talks below for more information.
Agenda:
6:30-6:55 pm Introductions & Social Time
6:55-7 pm R-Ladies New York Announcements
7:10-7:40 It's Time to Shine with timetrackR App, Jessica Lavery
7:40-8:10 Creating publication-ready & reproducible analytical tables with gtsummary, Margie Hannum
8:10-8:30 Networking
Title: It's Time to Shine with the timetrackR App
Presenter: Jessica Lavery
While tracking time may seem like a mundane task that in & of itself consumes your time, if monitored & assessed regularly it can be useful to create a record of your work & to identify potential areas for improving efficiency. The timetrackR Shiny app provides a high-level summary of active, inactive & upcoming projects, as well as visualizations for the percentage of time spent by project or project investigator, number of hours spent on each project, & a timeline framing each project's trajectory from planning through analysis & manuscript preparation. With the option to filter by year, investigator & analyst, the app is versatile enough to use for an individual or for an entire team as well as for use on a regular basis & for year-end or longer-term reviews of how time was spent. I will highlight the key features of the app & demonstrate how to integrate into your current workflow.
About Jessica: Jessica Lavery is a Biostatistician in the Department of Epidemiology & Biostatistics at Memorial Sloan Kettering Cancer Center. She has an MS in Biostatistics from the University of North Carolina at Chapel Hill (2014) & as of Fall 2019 is also pursuing a doctorate in public health (DrPH) in Biostatistics at Columbia University. Her research focuses primarily on retrospective analyses using institutional & claims data sources. She also serves as the[masked] Volunteer Coordinator for the Caucus for Women in Statistics. Follow her on Twitter @jessicalavs
Title: Creating publication-ready & reproducible analytical tables with gtsummary
Presenter: Margie Hannum
A critical aspect of many data analysis projects is presenting tables of summary statistics & regression model results. However, summarizing results into publication-ready tables often requires a lot of extra code to customize (e.g. create reference line for categorical variables, format p-values a certain way, bold variable labels, merge multiple model results into one table, etc.). The {gtsummary} package provides an elegant & flexible way to make summary & analytic tables in R. Written as a companion to the {gt} package from RStudio, the {gtsummary} package summarizes data sets, regression models, & more, using sensible defaults with highly customizable capabilities. It also allows you to pull values straight from these tables for use in inline text so that every portion of your R markdown analysis report is reproducible. This talk will go over the functionality of the {gtsummary} package, & how you can use it to create beautifully formatted, ready-to-share summary & result tables in a single line of R code.
About Margie: Margie Hannum is a Biostatistician at Memorial Sloan Kettering Cancer Center in the Department of Epidemiology & Biostatistics. Her research collaborations largely involve using multi-modal genomic & single cell data to characterize cancer subpopulations. She contributes to the {gtsummary} package & uses it every day in her analysis pipelines. Twitter: @Margaret_Hannum
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