Join @brucedesmarais.bsky.social for "Machine Learning" Feb. 5-7 to learn how #machinelearning can be used to uncover valuable insights, identify optimal model structures, perform variable selection, and deliver highly accurate predictions from data.

Join @hudsongolino.bsky.social for "LLM Text Generation in R: Practical Prompt Engineering" on Jan. 28-29. In 8 hours (over 2 days), you'll learn to integrate #LLM models with #Rstats, engineer effective prompts, and apply LLMs to real research tasks and data analysis.

Transition from using #Stata to using #Rstats independently in only 8 hours (over 2 days)! Join "R for Stata Users" with Andrew Miles on Jan. 22-23. Discover how R "thinks" and explore the differences in terminology, code syntax, data management, and default procedures.

Learn to uncover hidden structures & patterns in your research using "Latent Class Analysis" (#LCA) w/ Drs. Lanza & Bray on Jan. 22-24. You'll learn to apply LCA to inform theory, guide interventions, contribute to evidence-based decision-making, & extract new insights from data.

Transform how you design and analyze experiments in “Using AI to Build Better Experiments,” with Charles Crabtree on Jan. 14-16. Discover how to use #LLMs to create materials, augment studies, and interpret results.

Using #AI to write #machinelearning code? It can speed up your coding workflow, but you can’t always trust the accuracy or rigor of AI-generated code. Read @brucedesmarais.bsky.social's SH blog post for 5 checks to improve accuracy, evaluation, and interpretation.

Join Kenneth A. Bollen for "How to Choose a Model for Longitudinal Data", January 14-16. Gain invaluable insights and practical skills for comparing, selecting, and fitting the best #longitudinal models for repeated measures.

Learn to use structural equation modeling (SEM) to estimate dynamic panel data models w/ Paul Allison. "Longitudinal Data Analysis Using #SEM" begins Jan. 12. This 4-week on-demand seminar introduces maximum likelihood with SEM software (ML-SEM) using #Mplus, #Stata, SAS, and #Rstats.

Looking for a comprehensive way to manage, manipulate, analyze, & visualize your data in #Rstats? Join "Data Wrangling with the Tidyverse" with @kjhealy.co, January 7-9, to get hands-on experience w/ R's #tidyverse tools to accomplish everyday statistical analysis tasks.

Looking for a practical intro to designing effective web surveys & working with online respondents? Join "Designing Effective Online Surveys", taught by Andrew Miles on Jan. 7-9, for actionable design strategies, plus advantages & disadvantages of online samples.

Join “Applied Bayesian Data Analysis: A Second Course,” Dec. 10-12 with Roy Levy. Strengthen your ability to build, estimate, and interpret #Bayesian models for complex applied research.

See how @kjhealy.co builds trustworthy visualizations at #positconf2025 —then level up your own skills in his course on "Data Wrangling with the #Tidyverse", Jan. 7–9.

Join “Latent Growth Curve Modeling,” Dec. 10-12 with @dmcneish.bsky.social. Learn how to model change over time, understand growth factors, and apply growth models in your research.

Struggling with missing data? Join Paul Allison for "Missing Data Using R", a 4-week on-demand seminar starting Nov. 17. You'll learn maximum likelihood & multiple imputation—two of the most powerful #missingdata solutions using #Rstats.

Join Roy Levy on Dec. 10-12 for "Applied Bayesian Data Analysis: A Second Course" to take your #Bayesian skills to the next level! Master key skills in advanced modeling frameworks, including factor analysis, structural equation models, and multilevel models.

Check out the Data Science at Home podcast for insights on AI, machine learning, and tech innovation. Listen to the latest episode here.

Learn to model change or growth in #longitudinal data using "Latent Growth Curve Modeling" with @dmcneish.bsky.social, December 10-12. You'll walk away with the ability to confidently apply and interpret these methods to answer your unique research questions.

Distinguished Speaker Kosuke Imai presents "Evaluating AI & Machine Learning Algorithms for #causalinference", Feb. 10. Learn to assess #AI & #machinelearning practically—from heterogeneous treatment effects, individualized treatment rules, & human–AI collaboration.

Distinguished Speaker Kosuke Imai presents "Evaluating AI & Machine Learning Algorithms for #causalinference", Feb. 10. Learn to assess #AI & #machinelearning practically—from heterogeneous treatment effects, individualized treatment rules, & human–AI collaboration.

Join Simon Brewer on December 4-6 for "Spatial Analysis of Health Data"! Explore how geospatial #healthdata provide the tools to better understand & tackle public health challenges while addressing the issues that can arise while working with this type of data.

Forecasting requires tools built for time series. ARIMA (AutoRegressive Integrated Moving Average) models capture trends & seasonality where regression fails. Read more on the SH blog, then join Fundamentals of Time Series Analysis w/ Daniel J. Henderson, Nov. 12-14.

Want to improve or expand how you analyze #qualitative research—integrating computational tools & AI? Join Corey M. Abramson Dec. 3–5 for "Computer-Assisted Qualitative Data Analysis with Automation & AI". Ideal for those new to QDA software or coding.

Join "Mediation and Moderation Analysis for Simple Within-Subject Designs" with @akmontoya.bsky.social, Nov. 20-21. Using the MEMORE macro, created by the instructor, learn cutting-edge methods for estimating and interpreting effects in within-subject designs in 8 hours (over 2 days).

Join "Missing Data Using R" with Paul Allison starting Nov. 17. This 4-week on-demand seminar covers the theory and practice of maximum likelihood and multiple imputation, two of the latest and most accurate methods to handle #missingdata, all using #Rstats.

Join Daniel J. Henderson for "Fundamentals of Time Series Analysis" on November 12-14 for an introduction to time series methods for univariate and multivariate models. Learn how to program and apply these methods in practice using #Rstats and how to present results.

Join "Psychometrics" w/ @mattadiemer.bsky.social on Nov. 12-14 to learn about #psychometrics and how to to understand, detect, and remediate bias in measures. Topics include exploratory factor analyses, confirmatory factor analyses, MIMIC models, invariance & more.

What is the epigenome, and why does it matter? Find out in Jennifer Smith’s "Introduction to Epigenomics," Nov. 5-7. You'll learn to manage, clean, & model #epigenomic data, understand DNA methylation, and create & use biomarkers to enhance your health & environmental research.

Join "Latent Transition Analysis" on Oct. 31-Nov. 1 w/ Bethany Bray and Stephanie Lanza. Extend your latent class and latent profile analyses (LCA & LPA) skills to longitudinal data with LTA and learn how to examine how subgroup memberships change over time.

Distinguished Speaker, Benjamin Bolker (@bbolker.bsky.social), presents “Mixed Models in the Wild: Techniques, Workflows, and Challenges,” Nov. 18. He’ll cover core concepts, walk through modeling workflows, and address common challenges like sparse data and model complexity.

Earn your Measurement and Psychometrics Certification! Gain the skills and recognition that showcase your ability to design, test, and validate measures with confidence. Contact us to learn more.

Expand your #Python skillset w/ Adam Rennhoff’s "Python for #Rstats Users", Oct. 29-30. Discover how to leverage Python’s strengths within your familiar RStudio environment & take advantage of Python’s superior abilities to work with 'big data' and fit models.

Join Boris Nikolaev on Oct 22-23 for "Data Analysis with ChatGPT: A Practical Introduction"! Explore the strengths and limitations of ChatGPT as a data analysis tool in real-world scenarios to work with complex data and create compelling visualizations.

Learn to create and publish a professional, data-focused website in “Create an Online Presence with Quarto Websites” on October 16-17, with @andrew.heiss.phd‬! Discover how to use #Quarto to build a variety of websites like personal portfolios, research compendiums, and interactive dashboards.

From disease surveillance to healthcare access, spatial analysis transforms health research. See how in Simon Brewer’s "Spatial Analysis of Health Data" seminar, Dec. 4-6--learn mapping, regression, & spatiotemporal methods. View the 1st hour now: youtu.be/7vUiqoCiqsE

Discover how to apply mediation & moderation analysis in within-subject designs. Join @akmontoya.bsky.social's seminar Nov. 20-21 to learn to interpret & estimate total, direct, indirect, and conditional effects using the MEMORE macro, developed by the instructor. Watch the first hour now.

Are you interested in learning how to implement structural equation modeling (SEM) methods in your research? Join "Structural Equation Modeling Done Right" w/ Rex B. Kline, Oct. 15-17 to distinguish your own work in #SEM by following best practices and avoiding common mistakes.

Looking to estimate #causal effects from observational data? (You probably are!) Join @stephenvaisey.com for "Treatment Effects Analysis" starting Oct. 13. This 4-week on-demand seminar covers methods like propensity-score matching, inverse probability weighting, and entropy balancing.

Learn how to create and validate psychometric scales using #AI and #Rstats. Join @hudsongolino.bsky.social for "Automatic Item Generation and Validation," Sept. 10–11. The first hour, now on YouTube, introduces the motivation and key concepts behind the method.

Join "Propensity Score Analysis: Advanced" w/ Shenyang Guo, Oct. 9-11, to strengthen your PSA skillset. Learn advanced PSA topics like Heckman's kernel-based matching, Hirano & Imbens's generalized model for dosage analysis, subclassification, & Rosenbaum sensitivity analysis.

Get certified in #AI! Learn ChatGPT, text generation & classification, prompt engineering, & more through 4 expert-led seminars—and gain an "AI-Enabled Data Analytics" credential that showcases your expertise & strengthens your CV. Contact for more info: bit.ly/ai-bsky-sh

Join "Multilevel and Mixed Models Using R" with @stephenvaisey.com on Oct. 8-10 for an intensive intro to multilevel models. Learn the (real) difference between fixed & random effects and how to combine the strengths of both into a single model using #Rstats.

Join "Introduction to Text as Data" with Amber Boydstun & @corystruthers.bsky.social on Oct. 1-3 to learn text-as-data methods, including how they work, how they can be applied, and common pitfalls to avoid by drawing on social science research and perspectives.

Learn #Rstats in 3 days with Andrew Miles! Join "Introduction to R for Data Analysis" on October 1-3 for hands-on experience using & tailoring R to your own research, with topics like R functions and coding in R, descriptive stats, bivariate plots, and linear models.

Is your team making decisions based on biased data? Propensity Score Analysis helps you compare “apples to apples” and find the true impact. Read the Statistical Horizons blog to see how—and join our Sept. 18-20 seminar to master these methods. bit.ly/psablog-sh

Watch the first hour of "Introduction to Epigenomics" with Jennifer Smith—now on YouTube. Join the full seminar Nov. 5–7 to learn how to analyze DNA methylation data, run epigenome-wide association studies (EWAS), and build #epigenetic biomarkers.

Looking to strengthen your research with AI tools? Join @ethanbusby.bsky.social on Sept. 25-27 for "Using Large-Language Models for Social Science Research"! Learn the fundamentals of large language models (like ChatGPT) and how to integrate them into your research.

Learn to analyze event-time data in "Survival Analysis", taught on-demand by Dr. Paul Allison starting Sept. 22. This 4-week self-paced course will cover topics like censoring, Kaplan-Meier estimation, Cox regression, discrete-time methods, competing risks, and repeated events.

Learn to estimate treatment effects w/ nonexperimental or observational data in "Propensity Score Analysis: Basics" w/ Shenyang Guo, Sept. 18-20. Covering estimating #propensityscores, classic & optimal matching, propensity score weighting, Abadie & Imbens’ matching estimators.

Join "Automatic Item Generation and Validation: A Network Integrated Approach using Large Language Models in R" on Sept. 10-11 with @hudsongolino.bsky.social to learn how to use artificial intelligence to create and validate questionnaires and scales!

Already have a background in social network analysis & looking to expand your knowledge? Join John Skvoretz for "Social Networks: Statistical Approaches" starting Sept. 8 to learn statistical methods for analyzing social network data using #Rstats in this 4-week on-demand course.