"Power Analysis & Sample Size Planning" w/ Christopher L. Aberson begins March 16! Join this 4-week on-demand seminar to learn practical power and sensitivity strategies to strengthen your approach to determining sample sizes across research designs.
Join Christopher L. Aberson on March 25-27 for "R for SPSS Users" to seamlessly transition from #SPSS to #Rstats! Gain insights from a long-time user of both programs, covering terminology, data import, visualizations, analyses, and more. Elevate your skills with practical solutions.
How are recent advances in #AI reshaping teaching and research? After leading his #MachineLearning seminar, @brucedesmarais.bsky.social shares his reflections in a new post on LinkedIn. Read it here:
Upgrade your marketing research! Join Jeffrey Dotson on March 25–27 for "AI-Enabled Marketing Research" and learn to use Google Gemini for #AI-driven qualitative analysis, intelligent survey design, and synthetic respondent methods.
Join @stephenvaisey.com on March 18–20 for "Longitudinal Data Analysis w/ #Stata and LLMs". Learn to analyze panel data using mixed models, two period difference-in-differences, fixed-effects models, between-within models, & dynamic panel models, w/ added #LLM support.
Distinguished Speaker James Berger presents "Objective Bayesian Analysis: History & Interfaces w/ Classical Statistics", April 14. Learn how objective #Bayesian and classical approaches diverged, why those differences matter, & what they mean for statistical evidence today.
How do researchers determine the sample size needed to address their research questions? Join "Power Analysis & Sample Size Planning" w/ Christopher L. Aberson to learn about power and sensitivity approaches for multiple research designs. This 4-week on-demand seminar starts March 16.
Join "Automatic Item Generation and Validation: A Network Integrated Approach using LLMs in #Rstats" on Mar. 11 & 13 with @hudsongolino.bsky.social to learn how to use artificial intelligence to create and validate questionnaires and scales!
Join @dmcneish.bsky.social for "Dynamic #StructuralEquationModeling", March 4-6! Explore DSEM, a cutting-edge framework that utilizes intensive longitudinal data to gain detailed insights into dynamic processes and variability within and between subjects.
Expand your social network analysis toolkit! Join John Skvoretz for "Social Networks: Statistical Approaches" starting Feb. 9. Learn how to test hypotheses and model network structure using #Rstats in this 4-week on-demand course.
Join "Machine Learning for Estimating Causal Effects" w/ @ashleynaimi.bsky.social on Feb. 25-27. Learn to use cutting-edge "double-robust" #machinelearning methods to estimate treatment effects, minimize biases, & avoid problems like the “curse of dimensionality.”
Join Boris Nikolaev on Feb. 19-20 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.
Join “Multilevel & Mixed Models w/ #Stata & ChatGPT” w/ @stephenvaisey.com, Feb. 18-20 for an intensive intro to multilevel models. Learn the (real) difference between fixed & random effects, how to combine both in a single model, & how #ChatGPT can help design, estimate, and interpret your models.
Get Certified in Machine Learning! This 4-course certification builds from #ML foundations to advanced, applied methods, with a focus on responsible evaluation and practical use. Gain hands-on #machinelearning skills and real-world expertise. Contact us:
Learn to use natural language processing (NLP) techniques & large language transformer models (#LLMs) for research applications. Join "Text Classification with LLMs in #Rstats" w/ @hudsongolino.bsky.social on Feb. 11-13.
Evaluating #AI in practice? Join Distinguished Speaker Kosuke Imai on Feb. 10 for "Evaluating AI and #MachineLearning Algorithms for #causalinference". Learn frameworks to assess algorithmic impact and improve decisions.
Already have a background in social network analysis & looking to expand your knowledge? Join John Skvoretz for "Social Networks: Statistical Approaches" starting Feb. 9 to learn statistical methods for analyzing social network data using #Rstats in this 4-week on-demand course.
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.
