Master Model Selection & Simplification in R — Live, Hands-On, 2 Days
https://www.prstats.org/course/model-selection-and-model-simplification-msms05/
*What you’ll gain:*
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Clarity on *model fit metrics* (likelihood, deviance, residuals)
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Confidence comparing *nested models* across linear, GLM, and mixed models
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Tools to avoid overfitting using *cross-validation* and *information
criteria (AIC, BIC, etc.)*
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Practical know-how of *variable selection techniques* — stepwise, ridge,
Lasso, elastic net
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Best practices on *model averaging vs simplification*
*Format & logistics:*
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*Dates:* 3–4 November 2025
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*Duration:* 2 days, 4 hours per day
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*Format:* Live online (UK time) — Sessions are recorded for later viewing
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*Investment:* £250 (early bird £225 for first 5 spots)
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*Prerequisites:* Basic familiarity with R & RStudio; some experience
with regression (lm, glm) helpful
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*Support included:*
• All code, slides, and datasets provided
• Bring your own data for hands-on work
• 30 days’ email support + access to session recordings
• Certificate of attendance awarded
*Instructor:*
*Dr Niamh Mimnagh*, experienced statistician bridging ecology, epidemiology
and data science.
*Who should attend:*
Researchers, data analysts, postgraduate students — anyone who routinely
fits statistical models and wants to move beyond “black box” modeling to
principled model evaluation, selection, and simplification.
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*Limited early bird slots — reserve your place now!*
Transform your modeling approach by combining theory, applied examples, and
hands-on coding in R.
--
Oliver Hooker PhD.
PR stats
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