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.

Join "Scale Construction and 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 @brucedesmarais 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 missing data methods have evolved—and what you need to know today.

RT @GolinoHudson: Come learn with me techniques of prompt engineering (July 10 and 11). You are going to learn the basics of LLMs, Prompt E….

Learn how to analyze regression models with binary, ordinal, nominal, and count dependent variables using #Stata or #Rstats from July 29-Aug 1 with @MizeTrenton! 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 data analysis 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 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 (Sept. 25–27), you'll explore prompt engineering & common-use cases like surveys & samples. Watch the 1st hour now!

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

Learn advanced structural equation modeling (#SEM) topics like instrumental variables, alternative estimation methods, multiple group models, & models for #longitudinaldata 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 Edwin Dalmaijer 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 @GolinoHudson 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 Nicholas Seewald July 8-11 for SMART Designs for Adaptive Interventions. Gain insights into the design, implementation, & analysis of sequential multiple assignment randomized trials (SMARTs). Acquire the skills needed to propose and implement a SMART in your own research.

Looking to improve your #Rstats skills? Join Andrew Miles on June 30–July 1 for Essential R Skills for Intermediate Users. This hands-on course will help you write cleaner code, debug, create functions, and streamline your research with practical & flexible R strategies!.

Learn to uncover, explain, & understand why #machinelearning models make certain predictions. Join Interpretable Machine Learning w/ Jens Hainmueller, June 24–27, & gain hands-on experience applying these methods to real-world data & boosting model transparency & trustworthiness.

Discover how to model intensive longitudinal data using #DynamicStructuralEquationModeling (DSEM) w/ @dmcneish18, Aug. 12-15. Learn modeling latent outcomes, testing mediation over time, analyzing dyadic data, & more. Watch the 1st hour now on YouTube.

Join Meta-Analysis w/ David Wilson June 24-27! Learn to conduct all aspects of a meta-analysis & gain skills to search for studies to include, code & extract data, compute effect sizes, estimate models, explore publication selection bias, & report results using @Stata or #SPSS.

RT @fourbeerspod: Also, shout-out to Statistical Horizons (@StatHorizons) for sponsoring this episode! Use the promo code BEERS to get 20%….