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Weighted HierArchical Benchmark Dose modeling for averaging meta dose-response data

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WHALB is a platform for Weighted Hierarchical Bayesian Benchmark Dose. It incorporates model averaging of bayesian hierarchical models for benchmark dose modeling.   
All script are based on R software.  Operatable under R_4.2.1    
Rstan is required for Bayesian modeling in WHALB. Check out Rstan homepage: https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started     

For use, please specify at the top of your script the following two directories:
*mywd:  the working directory where you want all the intermediate and output files to be stored. e.g. mywd = "C:/User/me/Working/"        
*fileDir: the source directory where R scripts and critical original data to be stored. e.g. fileDir = "C:/User/me/ImportantFiles/"     
*mywd and fileDir may be specified at the same directory. Both could accomendate HPC directories. Please contact the author for instructions.

WHALB_model_utilites.R is required for all other scripts in this project. It contains basic utility functions. Please make sure all required R packages are installed.
**WHALB_model_utilities.R must be stored in the fileDir directory**

Folders are organized by components.
  * Continous: stan model script for fitting continous response data
  * Priors: the elicitation and specification of WHALB priors for models included: 1) Continous.
  * Model_Averaging: implementation and evaluation of averaging meta hierarchical models
  * Plotting: visual illustration of WHALB fits against orginal data points

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