CU Data Week

We will provide tips on how to create a stats-friendly database. We will discuss how to set up a complex database (i.e. longitudinal databases). Additionally, we will give best practices for variable naming conventions and format consistency to improve any project.

Recording Link

Learn how to create reproducible tables and create a dynamic report using R. We will cover how to create different tables in R and how to use R Markdown to create a comprehensive data report. Example code will be provided after the session.

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We will expand on the plots presented in previous data visualization seminars. We will cover how to create data visualizations and how to combine multiple plots into one figure using ggplot2. Prior experience using R and watching the previous data visualization videos are recommended. Example code will be provided after the session.

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A walkthrough of the milestones in a project's lifecycle, highlighting key features and considerations. Learn about the Research Electronic Data Capture (REDCap) application for participant management and study design. In this session, we will discuss the different phases of a project: Development, Production, Analysis/Cleanup, and Completion.

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Learn how to use R to prepare data for analysis. We will cover data import and data cleaning using tidyverse. Prior experience with R is not required.

The lecture will describe pre- and post-training of LLM models with examples from open-source pre-trained models. Instructors will introduce current best practices in working with AI-based tools.

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Learn how to create flexible and dynamic SAS programs using SAS Macros.  We will cover the difference between a macro variable and macro program and introduce when you would use them and how to code.  Prior experience using SAS is recommended. Example code will be provided after the session.

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Two state health department epidemiologists will walk through their day-to-day work, with a focus on the strategies and processes used to move from an initial program data inquiry to a meaningful, actionable output. The session’s remaining time for Q&A and discussion.

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Learn how to use R for basic data management to prepare data for analysis.  We will cover importing data from Excel and CSV formats, creating and editing variables, and dataset manipulations. Prior programming experience in R is not required. Example code will be provided after the session.

Recording Link

Learn how to use SAS software for basic data management to prepare data for analysis. We will cover importing data from Excel and CSV formats, creating and editing variables, and dataset manipulations. Example code will be provided after the session.

Recording Link

We will provide tips on where to find a statistician to join your research team and how to foster a productive, strong working collaboration with them. Additionally, we will discuss how to show up for an effective kick-off meeting with your statistician.

Recording Link

Learn about the basics of the Research Electronic Data Capture (REDCap) application for participant management and study design. In this session, we will discuss access to REDCap, project creation and design, data collection, participant management, and exporting data.

Recording Link

Learn how to create reproducible tables and create a dynamic report using R. We will cover how to create different tables in R and how to use R Markdown to create a comprehensive data report. Example code will be provided after the session.

We will expand on the plots presented in previous data visualization seminars. We will cover how to create data visualizations and how to combine multiple plots into one figure. Prior experience using R and watching the previous data visualization video are recommended. Example code will be provided after the session.

Recording Link

Learn how to create flexible and dynamic SAS programs using SAS Macros.  We will cover the difference between a macro variable and macro program and introduce when you would use them and how to code.  Prior experience using SAS is recommended. Example code will be provided after the session.

Recording Link

We will provide tips on how to create a stats-friendly database. We will discuss how to set up a complex database (i.e. longitudinal databases). Additionally, we will give best practices for variable naming conventions and format consistency to improve any project.

Recording Link