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Bayesian Multilevel Modelling using brms for Ecologists (BMME01)

1 message · Oliver Hooker

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Oliver Hooker
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Bayesian Multilevel Modelling using *brms* for Ecologists (BMME01) ?
PR?StatsFrame ecological questions rigorously using *Bayesian multilevel
models in R*
https://www.prstats.org/course/bayesian-multilevel-modelling-using-brms-for-ecologists-bmme01/

Explore model building, uncertainty quantification, spatial and temporal
autocorrelation, and species distribution modelling through a *ten?session
live online course*, designed for ecologists using R.
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 Course Details & Format

   -

   *Next Session*: October?20?24 & October?27?31,?2025 (Monday?Friday)
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   *Duration*: 10 days ? ~4 hours/day = 40 hours total
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   *Schedule*: Live sessions conducted in UK time (GMT+1); all sessions
   recorded and available for later viewing, accommodating global participants
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   *Format*: Interactive learning via remote online classroom; lectures and
   Q&A, plus applied coding exercises

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Who It?s For & What You?ll Gain

Designed for ecologists, postgraduate researchers, analysts, and
early-career scientists with basic R/RStudio experience and fundamental
statistics knowledge.

By the end of the course, you?ll be able to:

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   Frame and implement *Bayesian inference*, including priors, posteriors,
   and credible intervals
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   Fit GLMs and hierarchical multilevel models using *brms*
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   Choose and interpret meaningful priors for ecological parameters
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   Diagnose and critique model fit with posterior predictive checks, WAIC,
   LOO-CV
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   Model non-Gaussian ecological data (counts, proportions, zero-inflation)
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   Account for *spatial and temporal autocorrelation* in hierarchical models
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   Build multivariate/joint species distribution models for community
   analysis
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   Visualize and clearly communicate uncertainty in model results

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? Fees & Registration

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   *Early bird (first 10 places)*: *?400*
   -

   *Standard fee*: *?450*


Ideal participants should be comfortable installing and using R and
RStudio, and have basic familiarity with functions, plotting (e.g.
ggplot2), and statistics like regression.
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Why Choose BMME01?

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   *Comprehensive curriculum*: From Bayesian fundamentals to advanced
   ecological modelling
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   *Focus on applied use*: Ecologically-relevant examples including
   spatial, temporal, count, and joint species modelling
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   *Expert-led sessions*: Topic-by-topic deep dives with practical exercises
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   *Flexible structure*: Live sessions with recordings ? rewind, revisit,
   and learn at your pace
   -

   *Learning continuity*: Bring and work with your data, and get feedback
   via guided exercises and peer interaction

------------------------------

Build multilevel models with *confidence*, interpret ecological data with
*nuance*, and communicate results with *clarity*.

Email oliver at prstats.org with any questions