Join Prof. Frank E. Harrell Jr. (Vanderbilt University), a leading authority in applied biostatistics and regression methodology, and Drew G. Levy, PhD, for an online seminar designed for PhD students and professional researchers seeking to strengthen their quantitative research practice. Drawing on Regression Modeling Strategies (Harrell, 2015) and the continuously updated online materials, this workshop covers contemporary approaches to specifying, fitting, validating, and interpreting multivariable regression models for prediction and inference. Participants will explore key challenges in empirical research, including nonlinearity and interactions, overfitting, missing data, model validation, causal inference-based model specification, comparisons between regression and machine-learning approaches, and modeling continuous, binary, ordinal, longitudinal, and survival outcomes. With a strong emphasis on principled model formulation, graphical interpretation, reproducible workflows, and applied R examples using the rms package, the seminar equips participants to produce more robust, transparent, and publishable analyses. The seminar is available via live Zoom sessions or asynchronously with recordings and materials, includes access to an expert-moderated Q&A forum, and provides an official Instats certificate of completion. #BayesianStatistics #Biostatistics #CausalInference #ComputationalStatistics #DataScience #Epidemiology #HealthSciences #LongitudinalDataAnalysis #MachineLearning #MissingData #RegressionModelingStrategies #Statisticalmodellingandregression #Statistics #PublicHealth #R #Research #ResearchTraining #Instats

Easton's Nook is an intimate urban writing and arts retreat space where scholars, artists, and activists can meet, and can pursue their work individually or as a part of small, supportive, collaborati...

Join our two-day intensive online workshop on analyzing intensive longitudinal data from diary and ESM/EMA studies, led by Professor Scott Colwell (University of Guelph; Enablytics). Designed for PhD students, academic researchers, and applied professionals in the social and health sciences, this hands-on seminar will guide you from raw diary data to publication-ready models and APA-style reporting using R/RStudio and Mplus. You’ll learn how to prepare and visualize intensive longitudinal data, make principled decisions about centering and variance decomposition, estimate multilevel models with random intercepts and slopes, model lagged and dynamic processes, test moderation, cross-level interactions, and within-person mediation, address missing data, conduct simulation-based power analyses, and build reproducible reporting pipelines. The workshop combines short lectures with extended lab sessions using real diary datasets, and participants receive example data, R scripts, Mplus input files, diagnostics, and reporting templates that can be adapted directly for dissertations, manuscripts, and grant proposals. Live sessions are delivered via Zoom, with recordings and all materials available for 30 days after the seminar, plus access to a monitored Q&A forum and an official Instats certificate of completion. #ConsumerResearch #DataAnalytics #Epidemiology #LongitudinalDataAnalysis #Management #Psychology #Psychometrics #PublicHealth #Statisticalmodellingandregression #Statistics #Education #DataScience #Biostatistics #R #RStudio #Research #ResearchTraining #Instats

Strengthen the credibility and impact of your empirical research with our online seminar on contemporary regression modeling strategies for PhD students and professional researchers. Drawing on Frank E. Harrell Jr.’s Regression Modeling Strategies and taught by Prof. Harrell, with causal inference-based model specification led by Drew G. Levy, PhD, this workshop covers principled approaches to specifying, fitting, validating, and interpreting multivariable regression models for prediction and inference. Participants will explore key challenges in quantitative research, including nonlinearity and interactions, overfitting, missing covariates, model validation, comparisons with machine learning, and modeling for continuous, binary, ordinal, longitudinal, and survival outcomes. Through focused instruction, applied case studies, and reproducible R-based examples using the rms package, attendees will learn practical strategies for spline modeling, shrinkage and penalization, bootstrap and cross-validation, causal-informed variable selection, and publication-ready visualization of complex model results. The seminar is available live via Zoom or asynchronously with recordings and materials, includes access to a monitored Q&A forum after the live sessions, and provides an official Instats certificate of completion. #BayesianStatistics #Biostatistics #CausalInference #ComputationalStatistics #DataScience #Epidemiology #HealthSciences #LongitudinalDataAnalysis #MachineLearning #MissingData #RegressionModelingStrategies #Statisticalmodellingandregression #Statistics #PublicHealth #R #Research #ResearchTraining #Instats

Strengthen your quantitative research practice with this online seminar on contemporary regression modeling strategies for PhD students and professional researchers, taught primarily by Prof. Frank E. Harrell Jr. of Vanderbilt University, with a dedicated component on causal inference-based model specification led by Drew G. Levy, PhD. Drawing on Regression Modeling Strategies and the updated online materials, the seminar covers principled approaches to specifying, fitting, validating, and interpreting multivariable regression models for prediction and inference across continuous, binary, ordinal, longitudinal, and survival outcomes. Participants will explore key challenges in empirical research, including nonlinearity and interactions, overfitting, missing or partially observed covariates, variable selection, shrinkage and penalization, Bayesian and semiparametric ordinal models, model validation using bootstrap and cross-validation, graphical interpretation, and comparisons between statistical regression and machine-learning approaches. With worked case studies, reproducible R examples, and guidance using the rms package, this seminar is designed to help researchers produce more robust, transparent, and publication-ready analyses. Live sessions are offered via Zoom, with recordings, materials, and an expert-monitored Q&A forum available for continued learning after the seminar. An official Instats certificate of completion is provided, with ECTS Equivalent points available where applicable. #BayesianStatistics #Biostatistics #CausalInference #ComputationalStatistics #DataScience #Epidemiology #HealthSciences #LongitudinalDataAnalysis #MachineLearning #MissingData #RegressionModelingStrategies #Statisticalmodellingandregression #Statistics #PublicHealth #R #Research #ResearchTraining #Instats

Are you working with diary, ESM, or EMA data and want to move from raw intensive longitudinal datasets to publication-ready models? Join this two-day online workshop with Professor Scott Colwell (University of Guelph; Enablytics), designed for PhD students, academics, and applied researchers who want to test within-person processes, temporal dynamics, contextual effects, and individual heterogeneity using rigorous and reproducible methods. Through hands-on labs in R/RStudio and Mplus, participants will learn how to wrangle and visualize diary data, apply centering strategies, estimate random intercept and random slope models, model lagged and dynamic processes, test moderation, mediation, and cross-level interactions, handle missing data, conduct simulation-based power analyses, and produce APA-style reporting with reusable code and templates. The seminar combines short lectures, live Q&A, troubleshooting, example datasets, scripts, and reporting resources, with recordings and materials available for 30 days after the seminar for flexible review or asynchronous participation. Participants will leave with practical skills for designing stronger diary/ESM/EMA studies, implementing multilevel and dynamic models, diagnosing estimation issues, and translating seminar examples directly into dissertations, manuscripts, and grant proposals. An official Instats certificate of completion is provided. #ConsumerResearch #DataAnalytics #Epidemiology #LongitudinalDataAnalysis #Management #Psychology #Psychometrics #PublicHealth #Statisticalmodellingandregression #Statistics #Education #DataScience #Biostatistics #R #RStudio #Research #ResearchTraining #Instats

Advance your empirical research with an intensive online seminar on contemporary strategies for multivariable regression modeling for prediction and inference, led by Prof. Frank E. Harrell Jr. (Vanderbilt) with causal-inference sessions by Drew G. Levy, PhD. The course covers principled model formulation, handling nonlinearity and interactions (splines and smoothers), avoiding overfitting (shrinkage, penalization, resampling validation), missing and partially observed covariates, Bayesian and semiparametric ordinal approaches, and modeling for continuous, binary, longitudinal, and time-to-event outcomes—plus comparisons with machine-learning alternatives. Practical, reproducible workflows with R (rms package), worked case studies, publication-ready graphics, and R code are emphasized; prior competence with ordinary multiple linear regression is expected. Live-streamed via Zoom with recordings and materials available, a 30-day expert-monitored Q&A forum, on-demand access for 30 days after activation, and a certificate of completion (ECTS equivalent where indicated) are provided. Ideal for PhD students and professional researchers seeking to strengthen methodological skills and produce more credible, publishable analyses—register now to secure your place. #BayesianStatistics #Biostatistics #CausalInference #ComputationalStatistics #DataScience #Epidemiology #HealthSciences #LongitudinalDataAnalysis #MachineLearning #MissingData #RegressionModelingStrategies #Statisticalmodellingandregression #Statistics #PublicHealth #R #Research #ResearchTraining #Instats

Join a two-day intensive workshop with Professor Scott Colwell (University of Guelph; Enablytics) to master intensive longitudinal methods for diary and ESM/EMA data—designed for PhD students, academics, and applied researchers across the social and health sciences. Through hands-on labs in R/RStudio and Mplus you’ll learn to wrangle and visualize burst data, implement centering and multilevel models, model temporal dynamics (autoregressive, cross‑lagged, VAR/DSEM), handle missingness, run simulation-based power analyses, and produce reproducible, publication-ready APA reporting and code templates you can apply directly to dissertations, papers, and grant proposals. The workshop balances conceptual clarity and practical implementation, provides example data, Mplus input files, and R scripts, and includes live Zoom sessions plus recordings, materials, and an expert-moderated Q&A forum available for 30 days after the seminar; a certificate of completion (with ECTS equivalency where indicated) is provided. Prior familiarity with regression and multilevel concepts is recommended; R/RStudio and Mplus (or Mplus Demo) should be installed before the course. #ConsumerResearch #DataAnalytics #Epidemiology #LongitudinalDataAnalysis #Management #Psychology #Psychometrics #PublicHealth #Statisticalmodellingandregression #Statistics #Education #DataScience #Biostatistics #Sociology #R #RStudio #Research #ResearchTraining #Instats

Join a two-day intensive workshop with Prof. Scott Colwell (University of Guelph; Enablytics) on analyzing intensive longitudinal data from diary and ESM/EMA studies—hands-on labs in R (RStudio) and Mplus will take you from raw datasets to publication-ready models and APA-style reporting. You’ll learn data wrangling and visualization, centering and variance decomposition, multilevel models (random intercepts/slopes), lagged and dynamic models (AR, CL, VAR/DSEM), within-person mediation, moderation and cross-level interactions, principled missing-data approaches, and simulation-based power analyses—delivered with reproducible code, Mplus input files, diagnostics, and reporting templates so you can apply methods directly to dissertations, papers, and grant proposals. Designed for PhD students, academics, and applied researchers, the course blends conceptual clarity with practical implementation; it’s delivered live via Zoom with recordings, materials, and a monitored Q&A forum available for 30 days after the seminar, and participants receive a certificate of completion (ECTS-equivalent where indicated). Prior familiarity with regression and multilevel concepts is helpful; setup instructions and pre-work for R, RStudio, and Mplus are provided. #ConsumerResearch #DataAnalytics #Epidemiology #LongitudinalDataAnalysis #Management #Psychology #Psychometrics #PublicHealth #Statisticalmodellingandregression #Statistics #Education #DataScience #Biostatistics #R #RStudio #Research #ResearchTraining #Instats

Interested in mastering intensive longitudinal methods for your dissertation or research program? Join Professor Scott Colwell (University of Guelph; Enablytics) for a two-day intensive, hands-on workshop that takes you from raw diary/ESM/EMA data to publication-ready models and APA-style reporting using Mplus and R/RStudio. Designed for PhD students, academic researchers, and applied scientists, the seminar covers data wrangling and visualization, centering and variance decomposition, multilevel random intercepts/slopes, lagged and dynamic models (VAR/DSEM), moderation, within-person mediation, principled missing-data methods, simulation-based power analyses, and reproducible reporting templates—plus live troubleshooting, code, and exemplars you can adapt immediately. Sessions are livestreamed via Zoom with 30-day access to recordings, materials, and a monitored Q&A forum; participants receive example data, Mplus input and R scripts, and a certificate of completion (ECTS-equivalent where indicated). Register to build the practical skills needed to design diary studies, implement advanced longitudinal analyses, diagnose estimation issues, and produce transparent, reproducible pipelines for theses, grants, and journal papers. #ConsumerResearch #DataAnalytics #Epidemiology #LongitudinalDataAnalysis #Management #Psychology #Psychometrics #PublicHealth #Statisticalmodellingandregression #Statistics #Education #DataScience #Biostatistics #R #RStudio #Research #ResearchTraining #Instats

Join Scott Colwell (University of Guelph; Enablytics) for a two-day intensive, hands-on workshop on designing, analyzing, and reporting diary and ESM/EMA studies—perfect for PhD students, academic and applied researchers who want to move from raw intensive longitudinal data to publication-ready models. You’ll learn practical skills in R (RStudio) and Mplus—data wrangling and visualization, centering and variance decomposition, multilevel random effects, lagged/dynamic models (VAR/DSEM), moderation, within-person mediation, principled missing-data strategies, simulation-based power, and APA-style reporting—with reproducible code, Mplus input files, templates, and diagnostics. The format mixes short lectures with extended lab sessions using real datasets; livestreamed via Zoom with recordings and all materials available for 30 days after the seminar, plus a monitored Q&A forum and a certificate of completion (ECTS equivalent points indicated for European students where shown). Prior knowledge of basic regression/multilevel concepts is recommended; R familiarity is helpful but intro materials and setup instructions are provided. Register to gain immediately actionable competencies to design diary studies, select and implement appropriate models, and convert seminar examples directly into dissertations, manuscripts, and grant proposals. #ConsumerResearch #DataAnalytics #Epidemiology #LongitudinalDataAnalysis #Management #Psychology #Psychometrics #PublicHealth #Statisticalmodellingandregression #Statistics #Education #DataScience #R #RStudio #Research #ResearchTraining #Instats

Calling PhD students and researchers working with diary, ESM/EMA, or other intensive longitudinal data: join a two-day hands-on workshop with Professor Scott Colwell (University of Guelph; Enablytics) to move from raw diary datasets to publication-ready multilevel and dynamic models using R (RStudio) and Mplus. You’ll learn practical skills in data wrangling and visualization, centering and variance decomposition, random intercepts/slopes, lagged and VAR/DSEM models, moderation, within-person mediation, principled missing-data handling, simulation-based power, and APA-style reporting—complete with reproducible R and Mplus code, diagnostics, and report templates. The seminar combines short lectures with extended lab time, live Q&A and breakout support, 30-day access to recordings and materials, a monitored post-seminar Q&A forum, and a certificate of completion (ECTS-equivalent noted where applicable). Ideal for doctoral candidates and applied researchers who want immediately actionable competencies to apply to dissertations, grants, and high-tier publications—register now to secure your spot. #ConsumerResearch #DataAnalytics #Epidemiology #LongitudinalDataAnalysis #Management #Psychology #Psychometrics #PublicHealth #Statisticalmodellingandregression #Statistics #Education #DataScience #R #RStudio #Research #ResearchTraining #Instats

Unlock the potential of longitudinal data analysis in your research with a free, expert-led workshop by Dr. Tuhin Sheikh from Arizona State University. Specifically geared towards PhD students and professional researchers, this session will equip you with robust techniques using R, the go-to tool for statistical analysis. Dive deep into understanding temporal patterns and causal relationships, essential for impactful health and social sciences research. From preparing datasets to fitting linear mixed effects models, this hands-on workshop promises to enhance your analytical skills and research acumen. Engage with interactive sessions, real-world case studies, and expert Q&A, all designed to provide you with a competitive edge in academia. Join us live via Zoom or revisit the seminar materials for up to 30 days post-event. Certificates of completion and ECTS-equivalent points are available. Don’t miss this opportunity to advance your research capabilities—register now! #PublicHealth #Biostatistics #Statistics #Biomedicine #HealthEconomics #HealthSciences #PopulationHealthScience #ResearchinHealthSciences #LongitudinalDataAnalysis #R #Research #ResearchTraining #Instats

Unlock the power of longitudinal data analysis in your research with our free online workshop led by Dr. Tuhin Sheikh from Arizona State University's Biostatistics department. Designed specifically for PhD students, academics, and professional researchers, this workshop will equip you with essential skills to conduct robust longitudinal research using R. Master the intricacies of longitudinal study designs, prepare and visualize datasets, and apply sophisticated statistical models to gain meaningful insights into temporal patterns and causal relationships. Join us for an interactive learning experience and enhance your ability to publish high-impact research and secure research grants effectively. The workshop is available live via Zoom and asynchronously for your convenience, with a wealth of resources accessible online. Upon completion, you'll receive a certificate and, if applicable, ECTS Equivalent points. Don't miss this opportunity to advance your research capabilities! #PublicHealth #Biostatistics #Statistics #Biomedicine #HealthEconomics #HealthSciences #PopulationHealthScience #ResearchinHealthSciences #LongitudinalDataAnalysis #R #Research #ResearchTraining #Instats