🤩PREPRINT OUT! Using our causal model of 👫 growth, we test if model can estimate growth trajectories of pops. of 🚸 of uncertain age using cross-sectional data. Results: our model provide accurate estimates providing a solution for bioarcheological and other contexts!
www.biorxiv.org/content/10.6...
What a great addition to the existing literature! I wonder what's next, could an abm be brewing?
Everyone needs colleagues that appreciate the need to judge cakes, here in Danish festelavnsboller style
Very much looking forward to the upcoming Garrod Seminar Series themed 'Artificial Intelligence & the Past's Future' with some fantastic speakers (see below!). You can attend the seminar series online via Zoom (registration link: talks.cam.ac.uk/show/index/1...) - starting this Thursday!
**Part 1: From Bayesian inference to Bayesian workflow** 1. Bayesian theory and Bayesian practice 2. Statistical modeling and workflow 3. Computational tools 4. Introduction to workflow: Modeling performance on a multiple choice exam **Part 2: Statistical workflow** 5. Building statistical models 6. Using simulations to capture uncertainty 7. Prediction, generalization, and causal inference 8. Visualizing and checking fitted models 9. Comparing and improving models 10. Statistical inference and scientific inference **Part 3: Computational workflow** 11. Fitting statistical models 12. Diagnosing and fixing problems with fitting 13. Approximate algorithms and approximate models 14. Simulation-based calibration checking 15. Statistical modeling as software development
**4. Case studies** 16. Coding a series of models: Simulated data of movie ratings 17. Prior specification for regression models: Reanalysis of a sleep study 18. Predictive model checking and comparison: Clinical trial 19. Building up to a hierarchical model: Coronavirus testing 20. Using a fitted model for decision analysis: Mixture model for time series competition 21. Posterior predictive checking: Stochastic learning in dogs 22. Incremental development and testing: Black cat adoptions 23. Debugging a model: World Cup football 24. Leave-one-out cross validation model checking and comparison: Roaches 25. Model building and expansion: Golf putting 26. Model building with latent variables: Markov models for animal movement 27. Model building: Time-series decomposition for birthdays 28. Models for regression coefficients and variable selection: Student grades 29. Sampling problems with latent variables: No vehicles in the park 30. Challenge of multimodality: Differential equation for planetary motion 31. Simulation-based calibration checking in model development workflow **Appendices** A. Statistical and computational workflow for Bayesians and non-Bayesians B. How to get the most out of Bayesian Data Analysis
Bayesian Workflow by
Andrew Gelman, Aki Vehtari, @rmcelreath.bsky.social with @danpsimpson.bsky.social, @charlesm993.bsky.social, @yulingy.bsky.social, Lauren Kennedy, Jonah Gabry, @paulbuerkner.com, @modrakm.bsky.social, @vianeylb.bsky.social
(in production, estimated copy-editing time 6 weeks)
Improving scientific practice can seem daunting. In this fantastic talk (and thread below), Julia Rohrer shares practical ways to communicate methodological insights to a wider audience of researchers.
The ENDOW project is seeking a Research Officer in Research Data Management to be based at the London School of Economics. - Oversee and extend our database covering geospatial, demographic, economic & social network data from 50+ communities in 30+ countries! - Contribute to research on the dynamics of social and economic inequality! - Join a stellar interdisciplinary team! - funded by the ESRC and the NSF [world map showing location of ENDOW communities; photos of some of the team members and some of the ENDOW communities showing their diversity
Research Officer in Research Data Management Salary from £43,277 to £48,220 pa inclusive of London allowance Fixed-term appointment for 18 months This research officer position is to work with Eleanor Power as part of the ongoing "ENDOW" project (Economic Networks and the Dynamics of Wealth Inequality), funded by the UKRI and US National Science Foundation. The research officer will be based in the Department of Methodology, a leading centre for research and education in social science research methods. While we expect this to be a full-time appointment, we are open to considering the possibility of a part-time appointment. The post entails overseeing and extending the database of the "ENDOW" project, which includes data from over fifty communities around the world, comprising economic, demographic, and social network data characterising each community, its resident households, and the individuals within them. The research officer will be responsible for the expansion of this database to include longitudinal data from each community site, implementing a robust data infrastructure to manage and curate this information. The research officer will work closely with Dr Power and data contributors to ensure data quality, standardisation, and appropriate governance. They will contribute to core analyses of the ENDOW project and develop tools and resources that will be of wide utility for the collection, curation, and analysis of cross-cultural data. This role is central to building the data infrastructure that will enable meaningful, productive comparisons across these diverse field sites and will ultimately serve as a resource for the broader scientific community. The successful candidate will: Have a completed PhD, be close to completing a PhD, or have other research experience that demonstrates the capability to produce independent original research Have experience with database design, data management and data governance Have experience with programming in R or Python
🚨Job alert! The ENDOW project is hiring a Research Officer in Research Database Management, to be based at @lsemethodology.bsky.social.
Oversee & expand our database & contribute to research on social & economic inequality.
Deadline 15 February. Share & reach out!
jobs.lse.ac.uk/Vacancies/W/...
Picture of front cover of Theme Issue entitled "Transforming cultural evolution research and its application to global futures." The image on the front cover is of a Yao honey hunter in Mozambique holding retrieved honeycomb.
Today sees the publication of the Theme Issue featuring the CES Transformation Fund grant scheme. Enjoy! royalsocietypublishing.org/rstb/issue/3...
@durhamdcerc.bsky.social @durhamanthropology.bsky.social @cultevolfunding.bsky.social @culturalevolsoc.bsky.social
Quiet posters is also a great one!
📢 Here is my commentary about the pitfalls of taking an impoverished evolutionary approach to culture, which include 'the limitations of a unidirectional model of evolution' and 'the neglect of niche construction theory'. #ehbea #evolution #psychscisky 🧪
🧵 1/2
www.sciencedirect.com/science/arti...
Who has/has seen an internal llm usage policy for researchers that they think is good? Please share!
A photo of the Susan Welch Liberal Arts building at sunrise
📢 Come join us! Penn State Anthropology is hiring *two tenure-track assistant professors*, one in human reproductive ecology and one in archaeology. Here are just a few reasons why working at Penn State is awesome:
Miyagawa Shuntei's 1898 painting, "Playing Go (Japanese Chess)"
How to quantify the impact of AI on long-run cultural evolution? Published today, I give it a go!
400+ years of strategic dynamics in the game of Go (Baduk/Weiqi), from feudalism to AlphaGo!
Amazing! Many, many congratulations!
Part of an exciting special feature celebrating 50 years of quantitative cultural evolution!
Check out the rest here: bit.ly/CulturalEvolution
Illustration of a computational workflow for cultural evolution that connects abstract theory to real-world data. The arrows indicate logical and computational dependencies among theoretical, statistical, and scientific elements of a project. For example, an effective inferential model depends upon generative models, a question about those models (estimand), and the structure of the available evidence (sample).
Theorist bridge trolls barking at you to formally connect theory to data? Wondering how, without troll magic? We can help! "Bridging theory and data: A computational workflow for cultural evolution" With @dominikdeffner.bsky.social @natyfedorova.bsky.social Jeff Andrews. www.pnas.org/doi/10.1073/...
Great! Please add me :)
