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SUMMARY:PDHP Workshop: Model To Meaning: How To Interpret Statistical Models with marginaleffects
DESCRIPTION:\n\n\n\n\n\nPlease join for the next installment of the PDHP workshop series: Model To Meaning: How To Interpret Statistical Models with marginaleffects, presented by Vincent Arel-Bundock of the University Of Montreal.  Following the presenter’s book on the same topic, this workshop introduces the model to meaning conceptual framework, helping data analysis of all types to clearly and rigorously communicate model results, form (almost) any statistical model.  Relying on the key idea that raw parameter estimates can often be transformed into more interpretable quantities, the model to meaning framework provides a powerful toolset for analysts of all experience levels.\n\nTopics include:\n\n\nModel to meaning as a simple framework to clearly define and communicate your quantities of interest\nInterpreting the results of (almost) any statistical model with a single workflow and toolset\nComparing levels and effects across groups and scenarios to assess heterogeneity\nHands-on practice with the marginaleffects package in R and Python\n\n\n\n\n\nAs always, this workshop is free of cost and open to the public, so please feel free to distribute this message to others who may be interested.  For more information and to RSVP, please visit pdhp.isr.umich.edu/workshops.  Light refreshments will be served for those attending in-person. ISR Thompson St., Room 1430.\n\nFor video and resources from our past workshops, please check out the PDHP Youtube playlist and adjoining materials archive.\n\n\n\nClick to add event to Google Calendar\n\n\n\n\n\n\n\n
URL:https://psc.isr.umich.edu/events/causal-inference-248/
CATEGORIES:PDHP Workshop Series
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