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.

Learn #Bayesian methods with @roylevy.bsky.social in "Applied Bayesian Data Analysis", Sept. 4-6! Topics include model construction, graphical representation of models, model comparisons, Markov chain Monte Carlo (MCMC) estimation, & more.

Join "Bluesky Data: Collection, Cleaning, and Analysis" with @resulumit.bsky.social on Aug. 26-27! Learn to access the #Bluesky API, clean social media data, and apply text & network analysis using #Rstats in this hands-on course.

Discover how #Bayesian methods for #qualitativeresearch can help you formulate clear hypotheses, avoid biases, and draw well-supported conclusions using practical applications & case studies. Join "Bayesian Analysis for Qualitative Evidence" on Aug. 26-27, taught by Tasha Fairfield.

Join Dr. Gonzalo Vazquez-Bare on Aug. 19-22 for a course on the latest developments in #Difference-in-Differences. You will learn to apply classical and novel methods for estimating treatment effects and to evaluate the assumptions behind them.

Welcome our next Distinguished Speaker, John P. A. Ioannidis, for “Reproducible and Useful Research: The Replication Crisis and Solutions”, Aug. 11. Explore the causes of irreproducibility & learn practical, evidence-based ways to improve reliability.

Learn how to extend latent class analysis (LCA) to longitudinal data w/ "Latent Transition Analysis," Oct. 31-Nov. 1. Bethany Bray & Stephanie Lanza cover model selection, measurement invariance, predictions, & more. Watch the 1st hour now!

Explore Monte Carlo simulations, a valuable tool for understanding, evaluating, comparing, & applying a wide array of statistical methodologies. Join Ashley Naimi Aug. 19-22 for "Design & Analysis of Simulation Studies" to learn to implement your own simulation using #Rstats.

Looking to strengthen your #causalinference skills? Join @noahgreifer.bsky.social on Aug. 12-15 for "Causal Inference in R Using MatchIt and WeightIt" to gain the skills to apply these #Rstats packages to estimate and interpret treatment effects.

Join @dmcneish.bsky.social for "Dynamic #StructuralEquationModeling", Aug 12-15! Explore DSEM, a cutting-edge framework that utilizes intensive longitudinal data to gain detailed insights into dynamic processes and variability within and between subjects.

Curious how Python can expand your R workflow? Watch the first hour of "Python for #Rstats Users" with Adam D. Rennhoff, then join the Oct. 29–30 seminar to build hands-on #Python skills for data science, #machinelearning, and #deeplearning.

Learn to use natural language processing (NLP) techniques & large language transformer models - #LLMs - for research applications. Join "Text Classification with Large Language Transformer Models in #Rstats" w/ @hudsongolino.bsky.social on Aug. 5-8.

"My First R Package" Next week I’ll be giving a hands-on workshop on #RStats We'll start from scratch and build our very own 📦 Re-use go-to functions, boost reproducibility, and share code with colleagues. I always a blast teaching this and am excited to meet the new group! tinyurl.com/mv2hrd8n

Learn how to analyze panel data with @stephenvaisey.com. "Longitudinal Data Analysis Using #Rstats" will be taught on Aug. 5-8. We will cover mixed models, fixed-effects models, between-within models, and dynamic panel models.

Labeling data can be costly. Learn how active learning helps #machinelearning models perform better with fewer human annotations in "Supercharge Your Classifier Development with Active Learning", a blog post by Advanced ML instructor Bruce Desmarais.

Join "Scale Construction & Development" w/ Deborah Bandalos on July 29-Aug 1 to learn how to construct scales that produce accurate & reliable measurements. This seminar will take you from current best practices to exploratory factor analysis & confirmatory factor analysis.

Join Bruce Desmarais on July 29-Aug. 1 for "Advanced Machine Learning". Go beyond prediction— address causal inference, missing data, LLMs, and more by applying advanced #machinelearning methods using #Rstats.

Celebrate 20 years with Statistical Horizons! Paul Allison, founder & President, presents "Missing Data Then and Now", a FREE 3-hour Distinguished Speaker Series seminar on how #missingdata methods have evolved—and what you need to know today.

Learn how to analyze regression models with binary, ordinal, nominal, and count dependent variables using #Stata or #Rstats from July 29-Aug 1 with @trentonmize.bsky.social! Registration for "Categorical Data Analysis" is now open.

Join Boris Nikolaev on July 24-25 for "Data Analysis with ChatGPT: A Practical Introduction"! Explore the strengths and limitations of #ChatGPT as a #dataanalysis tool in real-world scenarios to work with complex data and create compelling visualizations.

Interested in creating your own #Rstats package? Learn how to organize code efficiently, manage dependencies, implement best practices in testing and documentation, and distribute your package with "My First R Package" taught by @vincentab.bsky.social on July 22-23!

Learn how to apply #LLMs like ChatGPT in real research. In "Using Large-Language Models for Social Science Research" w/ @ethanbusby.bsky.social (Sept. 25–27), you'll explore prompt engineering & common-use cases like surveys & samples. Watch the 1st hour now!

Join @lucystats.bsky.social for "Understanding Statistics in Medical Literature", July 22–25. Learn how to decode stats, visuals, and study design in clinical research.

Learn advanced #structuralequationmodeling (SEM) topics like instrumental variables, alternative estimation methods, multiple group models, & models for longitudinal data at your own pace. 4-week course SEM: Part 2 On Demand with Paul Allison starts July 21.

Learn the basics of #Python in 4 days! Join @dalmaijer.bsky.social for "Introduction to Python for Data Analysis" on July 15-18 to learn how to use Python for data analysis, including handling datasets and writing full analyses.

Learn how to apply #Bayesian reasoning to qualitative research in "Bayesian Analysis for Qualitative Evidence" with Tasha Fairfield (Aug. 26–27). Watch the first hour now and see how this method can improve #inference and clarity in your work.

Join "Machine Learning for Estimating #Causal Effects" w/ Ashley Naimi on July 15-18. Learn to use cutting-edge "double-robust" #machinelearning methods to estimate treatment effects, minimize biases, & avoid problems like the “curse of dimensionality.”

Join @hudsongolino.bsky.social for "LLM Text Generation in R: Practical Prompt Engineering" on July 10-11. 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.

Join @nickseewald.com on July 8-11 for "SMART Designs for Adaptive Interventions". Gain insights into the design, implementation, and analysis of sequential multiple assignment randomized trials (SMARTs). Acquire the skills needed to propose and implement a SMART in your own research.