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PhD-level seminar on No-Code Statistical Network Modeling with Moses Boudourides . Live Q&A plus on‑demand access. Join via your university’s Instats membership or enroll directly.

How can you model relationships and network change with methodological confidence—without needing to code? Join Professor Moses Boudourides for an online seminar introducing no-code statistical network modeling for researchers across the sciences and digital humanities. Through an interactive application and worked examples, you’ll explore static exponential-family random graph models (ERGMs), temporal ERGMs, and stochastic actor-oriented models (SAOMs), learning how to choose appropriate models, assess assumptions and diagnostics, and interpret results for scholarly research. Designed for PhD students, postdoctoral researchers, and academics, the seminar combines conceptual foundations with practical guidance on applying network analysis to your own research. Attend live via Zoom or learn asynchronously: recordings and materials are available for 30 days, with access to an expert-monitored Q&A forum during that period. Participants receive an Instats certificate of completion. disciplines #Sociology #DataScience #Statistics #Research #ResearchTraining #Instats

PhD-level seminar on No-Code Statistical Network Modeling with Moses Boudourides . Live Q&A plus on‑demand access. Join via your university’s Instats membership or enroll directly.

Join Instats for an online seminar on no-code statistical network modeling for PhD students, postdoctoral researchers, and professional academics who want to analyze relational data with greater methodological confidence. Led by Professor Moses Boudourides, this seminar introduces a rigorous, accessible framework for studying tie formation, network structure, and network change across the sciences and digital humanities. Participants will explore static ERGMs, temporal ERGMs, and stochastic actor-oriented models, learning how to connect research questions to appropriate model families, assess assumptions, interpret diagnostics, and communicate findings in publication-ready language. Using an interactive no-code Streamlit environment and worked examples, the seminar emphasizes both conceptual foundations and empirical applications, including visual inspection workflows, model specification, fit assessment, longitudinal network analysis, and common pitfalls in applied network modeling. Designed for researchers seeking to strengthen research design and expand their methodological toolkit, the seminar includes live Zoom access, 30-day access to recordings and materials, a monitored Q&A forum, and an official Instats certificate of completion, with ECTS Equivalent points available where applicable. disciplines #Sociology #DataScience #Statistics #Research #ResearchTraining #Instats

Creates publication-ready tables documenting exponential-family random graph models (ERGMs), a class of statistical models for social networks (Robins et al., 2007, &lt;<a href="https://doi.org/10.1016%2Fj.socnet.2006.08.002" target="_top">doi:10.1016/j.socnet.2006.08.002</a>&gt;). Tables describe model terms through their definitions, mathematical representations, and graphical representations, and can be generated from ERGM formulas or from models fitted with the 'ergm' package (Hunter et al., 2008, &lt;<a href="https://doi.org/10.18637%2Fjss.v024.i03" target="_top">doi:10.18637/jss.v024.i03</a>&gt;). Resulting tables can be integrated into 'quarto' and 'rmarkdown' documents.

Creates publication-ready tables documenting exponential-family random graph models (ERGMs), a class of statistical models for social networks (Robins et al., 2007, &lt;<a href="https://doi.org/10.1016%2Fj.socnet.2006.08.002" target="_top">doi:10.1016/j.socnet.2006.08.002</a>&gt;). Tables describe model terms through their definitions, mathematical representations, and graphical representations, and can be generated from ERGM formulas or from models fitted with the 'ergm' package (Hunter et al., 2008, &lt;<a href="https://doi.org/10.18637%2Fjss.v024.i03" target="_top">doi:10.18637/jss.v024.i03</a>&gt;). Resulting tables can be integrated into 'quarto' and 'rmarkdown' documents.

The use of exponential random graph models (ERGMs) is becoming prevalent in psychology due to their ability to explain and predict the formation of edges between vertices in a network. Valid inferenc...