Bayesian Hierarchical Modeling
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Learn how to fit and compare ecological models in a Bayesian hierarchical framework, which separates the observation process from the ecological process when estimating spatial and/or temporal variation in parameters such as abundance, density, and survival.
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A good understanding of probability and statistical methods
Experience with fitting models in R (e.g., Introduction to Ecological Statistics and Modeling and Generalized Linear, Additive, and Mixed Models)
Experience with fitting Bayesian models in R (e.g., Introduction to Bayesian Modeling)
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TOPICS
What is a hierarchical model?
Random effects and hyperparameters
Separating the observation process from the ecological process
Observation-process models for data from studies involving mark-recapture, distance sampling, occupancy, sightings of unmarked individuals, and citizen-science
What is a state-space model?
Spatial modelling of abundance/density, occupancy, and survival
Spatio-temporal modelling of abundance/density, occupancy, and survival
Allowing for spatial and/or temporal autocorrelation
Use of spatial and/or temporal covariates
Choice of priors
Checking model-fit
Comparing two or more models
LEARNING OUTCOMES
Understand how to separate the observation-process from the ecological-process
Understand which type of observation-process model is appropriate for your data
Gain experience fitting spatio-temporal models to your data in R
Understand how to check the fit of a spatio-temporal model in R
Be aware of the potential need to allow for spatial and/or temporal autocorrelation
Know how to compare the predictive ability of different spatio-temporal models
COURSE OPTIONS & INFORMATION (Review chart above, then click below)
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FORMAT:
3 months of access to course materials as you work at your own pace
CONTINUING EDUCATION:
16 CEUs with The Wildlife Society
Go to our Continuing Education Page for more details
DATES & PRICES:
Winter: Dec 2 - Feb 23 (Early bird ends Nov 4th): $275 student / $375 professional
*Early bird saves $75
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FORMAT:
3 months of access to course materials as you work at your own pace
Get instructor support for the 3-month term via email, discussion threads, group meetings, and one-on-one appointments
After working through the course materials, set up an optional meeting with the instructor to discuss your own personal project from work or school
CONTINUING EDUCATION:
16 CEUs with The Wildlife Society
Go to our Continuing Education Page for more details
CERTIFICATIONS:
Earn 1 credit toward certification as an Associate/Certified Wildlife Biologist® (at any level) with The Wildlife Society
DATES & PRICES:
Winter: Dec 2 - Feb 23 (Early bird ends Nov 4th): $425 student / $525 professional
*Early bird saves $75
-
FORMAT:
12 months of access to course materials as you work at your own pace
Get instructor support for the 3-month term via email, discussion threads, group meetings, and one-on-one appointments
After working through the course materials, set up an optional meeting with the instructor to discuss your own personal project from work or school
CONTINUING EDUCATION:
16 CEUs with The Wildlife Society
Go to our Continuing Education Page for more details
CERTIFICATIONS:
Earn 1 credit toward certification as an Associate/Certified Wildlife Biologist® (at any level) with The Wildlife Society
Earn 1 credit towards a professional certificate in Applied Quantitative Ecology with CWS
Earn an additional 1-2 academic credits with an Applied Project
Go to our Academic Credit Page for details
DATES & PRICES:
Winter: Dec 2 - Feb 23 (Early bird ends Nov 4th): $575 professional / $675 student
*Early bird saves $75
SCHOLARSHIPS
Full scholarships are available to participants from countries designated as “lower income” and “lower middle income” in the World Bank List of Economies. Please see our CWS World Scholars Program page for details.
CANCELLATION POLICY
Cancellations 30 days or more before the start date are not subject to cancellation fees. Cancellations <30 days before the start date are subject to a 50% cancellation fee. No refunds once the course begins.