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genentech
psborrow2:Bayesian Dynamic Borrowing Analysis and Simulation
Bayesian dynamic borrowing is an approach to incorporating external data to supplement a randomized, controlled trial analysis in which external data are incorporated in a dynamic way (e.g., based on similarity of outcomes); see Viele 2013 <doi:10.1002/pst.1589> for an overview. This package implements the hierarchical commensurate prior approach to dynamic borrowing as described in Hobbes 2011 <doi:10.1111/j.1541-0420.2011.01564.x>. There are three main functionalities. First, 'psborrow2' provides a user-friendly interface for applying dynamic borrowing on the study results handles the Markov Chain Monte Carlo sampling on behalf of the user. Second, 'psborrow2' provides a simulation framework to compare different borrowing parameters (e.g. full borrowing, no borrowing, dynamic borrowing) and other trial and borrowing characteristics (e.g. sample size, covariates) in a unified way. Third, 'psborrow2' provides a set of functions to generate data for simulation studies, and also allows the user to specify their own data generation process. This package is designed to use the sampling functions from 'cmdstanr' which can be installed from <https://stan-dev.r-universe.dev>.
Maintained by Matt Secrest. Last updated 2 months ago.
bayesian-dynamic-borrowingpsborrow2simulation-study
18 stars 7.87 score 16 scriptscran
SeaVal:Validation of Seasonal Weather Forecasts
Provides tools for processing and evaluating seasonal weather forecasts, with an emphasis on tercile forecasts. We follow the World Meteorological Organization's "Guidance on Verification of Operational Seasonal Climate Forecasts", S.J.Mason (2018, ISBN: 978-92-63-11220-0, URL: <https://library.wmo.int/idurl/4/56227>). The development was supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 869730 (CONFER). A comprehensive online tutorial is available at <https://seasonalforecastingengine.github.io/SeaValDoc/>.
Maintained by Claudio Heinrich-Mertsching. Last updated 10 months ago.
1.70 score