Whether you are a new researcher or a seasoned veteran, chances are you’re working with research data. Small changes to your data management practices can make a significant impact during research, and save time and effort when you are ready to share the results. In this session you’ll  learn about resources and practical steps you can take to organize and document your data during research, and how to increase the impact of your research while meeting publisher and funder expectations for sharing your data. Employing these practices will ensure that everyone, including you, can understand and work with your data in the weeks, months, and years to come.

Introduction to Social Network Analysis with R will introduce attendees to concepts of social network analysis by illustration. This in-person course will walk through R code, learning what the code does and introducing network concepts along the way. Attendees will leave with knowledge of commonly used R packages useful for network analysis. Beginner R knowledge is recommended.

This virtual workshop introduces factor analysis models to help participants better understand the methodologies used to develop scales and measures in research. Familiarity with general linear models (such as ANOVA and linear regression) is recommended, but no prior knowledge regarding factor analysis is required. The workshop will focus primarily on confirmatory factor analysis and its application to survey methodology. This is a virtual workshop and will be held over Zoom.

This virtual workshop will introduce how to visualize data in multiple ways using Stata. Various data visualization examples will be demonstrated during the workshop. By the end of this workshop, participants will be able to create and edit presentation or publication quality visualizations (e.g., bar graphs, box plots, scatterplots) using Stata code. This is an introductory workshop appropriate for those with only basic familiarity with Stata. Example code will be provided.

This workshop provides an applied overview of principles and methods for longitudinal data analysis, with hands-on examples in R. Topics include types of longitudinal data, data manipulation and visualization, statistical methods for longitudinal analysis (including mixed-effects models and structural equation models), longitudinal measurement invariance, handling missing data, and separating within-person and between-person effects. Participants are encouraged to bring a laptop with R and RStudio installed for interactive exercises. This workshop is intended for participants with experience using R and RStudio. Prior experience with longitudinal data analysis, though helpful, is not required.

This virtual workshop will introduce packages related to geospatial analysis to design a bivariate map in the R coding environment. By the end of this workshop, participants will be able to use geospatial packages in an R workflow to create a publication-quality bivariate map. A bivariate map helps to understand the spatial relationships, correlations, and patterns between two different spatial variables. This is an introductory workshop appropriate for those with only a basic familiarity with R and geospatial analysis. Example code will be provided. This is a virtual workshop and will be held over Zoom.

This workshop will introduce Python and foundational machine learning concepts, utilizing a dataset comprising textual content. Participants will learn the basics of coding in Python, set up a data science environment, and explore key machine learning concepts applied to text data. No prior experience with Python or machine learning is required. This is a virtual workshop and will be held over Zoom.

This workshop will examine how social scientists can use Large Language Models (LLM) to develop variables that can be used in statistical analyses by social scientists. As social scientists have gained access to an increasing amount of textual data, automated text analysis (ATA) has become one of their standard toolsets. LLM is another ATA tool, yet social scientists are just beginning to use it. This interactive and applied workshop explores how social scientists can use LLM to develop measures that can be used as variables in quantitative analyses. The workshop does not require any prerequisite knowledge and is open to all social scientists.