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DTSTART;TZID=Europe/London:20250305T100000
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DTSTAMP:20260625T162732
CREATED:20250120T114047Z
LAST-MODIFIED:20250120T114047Z
UID:10000490-1741168800-1741192200@www.swdtp.ac.uk
SUMMARY:Gen Delta Student Workshop
DESCRIPTION:This is free training workshop for women from Black\, Asian and other minoritised ethnic groups currently in postgraduate research (PGR) studies on ‘retention and progression’ at Goldsmiths\, University of London on Wednesday\, 5th March 2025 from 10:00 am to 4:30 pm. See flyer attached. \n  \nIn this workshop you will learn about the different funding opportunities available to undertake PGR research\, you will also develop skills in writing a research proposal for PGR study. Reimbursement of up to £125 per person will be offered for travel\, however\, please wait until your place is confirmed before booking travel. Catering will also be provided on the day. \n  \nTo learn more about this event\, please follow the link below. \n  \nFor questions or queries please email Anna Horn\, the Generation Delta project manager at a.e.horn@leeds.ac.uk. \n  \nWebsite: https://generationdelta.leeds.ac.uk/news/the-university-of-plymouth/ \nTwitter: https://twitter.com/GenDelta2022/status/1775475535642038561 \nLinkedIn: https://www.linkedin.com/feed/update/urn:li:activity:7181239189928058880
URL:https://www.swdtp.ac.uk/event-calendar/gen-delta-student-workshop/
CATEGORIES:Training,Webinar/Seminar/Symposium
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BEGIN:VEVENT
DTSTART;TZID=Europe/London:20250313T090000
DTEND;TZID=Europe/London:20250313T160000
DTSTAMP:20260625T162732
CREATED:20241204T143354Z
LAST-MODIFIED:20241204T143354Z
UID:10000485-1741856400-1741881600@www.swdtp.ac.uk
SUMMARY:Introduction to Longitudinal Data Analysis
DESCRIPTION:In this course you will learn both how to clean longitudinal data as well as the main statistical models used to analyse it. The course will cover three fundamental frameworks for analysing longitudinal data: multilevel modelling\, structural equation modelling and event history analysis. \nThe course is organised as a mixture of lectures and hands-on practicals using real-world data. During the course\, there will also be opportunities to discuss also how to apply these models in your own research. \n  \nOutcomes: \n\nTo gain competence in the concepts\, designs and terms of longitudinal research.\nTo be able to apply a range of different methods for longitudinal data analysis.\nTo have a general understanding of how each method represents different kinds of longitudinal processes.\nTo be able to choose a design\, a plausible model and an appropriate method of analysis for a range of research questions.\n\n\nTopics covered by session \n\n13.03.2025  – Data cleaning and visualization of longitudinal data \n21.03.2025 – Cross-lagged models (covering also an introduction to Structural Equation Modelling and auto-regressive models) \n28.03.2025 – Multilevel model of change (covering also an introduction to multilevel modelling) \n04.04.2025 –  Latent Growth Modelling \n11.04.2025  – Survival models (also known as event history analysis)
URL:https://www.swdtp.ac.uk/event-calendar/introduction-to-longitudinal-data-analysis/2025-03-13/
CATEGORIES:Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20250321T090000
DTEND;TZID=Europe/London:20250321T160000
DTSTAMP:20260625T162732
CREATED:20241204T143354Z
LAST-MODIFIED:20241204T143354Z
UID:10000486-1742547600-1742572800@www.swdtp.ac.uk
SUMMARY:Introduction to Longitudinal Data Analysis
DESCRIPTION:In this course you will learn both how to clean longitudinal data as well as the main statistical models used to analyse it. The course will cover three fundamental frameworks for analysing longitudinal data: multilevel modelling\, structural equation modelling and event history analysis. \nThe course is organised as a mixture of lectures and hands-on practicals using real-world data. During the course\, there will also be opportunities to discuss also how to apply these models in your own research. \n  \nOutcomes: \n\nTo gain competence in the concepts\, designs and terms of longitudinal research.\nTo be able to apply a range of different methods for longitudinal data analysis.\nTo have a general understanding of how each method represents different kinds of longitudinal processes.\nTo be able to choose a design\, a plausible model and an appropriate method of analysis for a range of research questions.\n\n\nTopics covered by session \n\n13.03.2025  – Data cleaning and visualization of longitudinal data \n21.03.2025 – Cross-lagged models (covering also an introduction to Structural Equation Modelling and auto-regressive models) \n28.03.2025 – Multilevel model of change (covering also an introduction to multilevel modelling) \n04.04.2025 –  Latent Growth Modelling \n11.04.2025  – Survival models (also known as event history analysis)
URL:https://www.swdtp.ac.uk/event-calendar/introduction-to-longitudinal-data-analysis/2025-03-21/
CATEGORIES:Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20250326T140000
DTEND;TZID=Europe/London:20250326T160000
DTSTAMP:20260625T162732
CREATED:20241204T140029Z
LAST-MODIFIED:20241204T140029Z
UID:10000476-1742997600-1743004800@www.swdtp.ac.uk
SUMMARY:Introduction to Bayesian Statistics for Social Scientists
DESCRIPTION:This course will familiarise students with the basic concepts of Bayesian theory. It is designed to provide an introduction to the principles\, methods\, and applications of Bayesian statistics. Bayesian statistics offers a powerful framework for data analysis and inference\, allowing for the incorporation of prior knowledge and uncertainty in a coherent and systematic manner. \n\nThe course covers: \n\nThe Basics of Probability\nBayes’ Theorem and Bayesian inference\nProbability Functions\nBayesian Conjugates\nMarkov Chain Monte Carlo\nApplications\n\n  \nBy the end of the course participants will: \n\nBe able to understand the basics of Bayesian analysis\nPerform simple Bayesian analyses\nApply simple models to their own work\n\n  \nThe course will be split across two days. On both days\, participants will work through a two-hour pre-recorded lecture in the morning and attend a two-hour live session at 2pm where they will have the opportunity to apply their learning to practical examples.
URL:https://www.swdtp.ac.uk/event-calendar/introduction-to-bayesian-statistics-for-social-scientists/2025-03-26/
CATEGORIES:Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20250328T090000
DTEND;TZID=Europe/London:20250328T160000
DTSTAMP:20260625T162732
CREATED:20241204T143354Z
LAST-MODIFIED:20241204T143354Z
UID:10000487-1743152400-1743177600@www.swdtp.ac.uk
SUMMARY:Introduction to Longitudinal Data Analysis
DESCRIPTION:In this course you will learn both how to clean longitudinal data as well as the main statistical models used to analyse it. The course will cover three fundamental frameworks for analysing longitudinal data: multilevel modelling\, structural equation modelling and event history analysis. \nThe course is organised as a mixture of lectures and hands-on practicals using real-world data. During the course\, there will also be opportunities to discuss also how to apply these models in your own research. \n  \nOutcomes: \n\nTo gain competence in the concepts\, designs and terms of longitudinal research.\nTo be able to apply a range of different methods for longitudinal data analysis.\nTo have a general understanding of how each method represents different kinds of longitudinal processes.\nTo be able to choose a design\, a plausible model and an appropriate method of analysis for a range of research questions.\n\n\nTopics covered by session \n\n13.03.2025  – Data cleaning and visualization of longitudinal data \n21.03.2025 – Cross-lagged models (covering also an introduction to Structural Equation Modelling and auto-regressive models) \n28.03.2025 – Multilevel model of change (covering also an introduction to multilevel modelling) \n04.04.2025 –  Latent Growth Modelling \n11.04.2025  – Survival models (also known as event history analysis)
URL:https://www.swdtp.ac.uk/event-calendar/introduction-to-longitudinal-data-analysis/2025-03-28/
CATEGORIES:Training
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