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Name: Joshua Soboil

Type: User

Company: @R-HTA-in-LMICS

Bio: Decision modelling | Probability | Health care

Twitter: ama_loop

Blog: https://jsoboil.github.io/

Some Bytes About Me:

Hi! I am a senior analyst in health economics and HTA at Cogentia and I focus on methods related to Health Technology Assessment (HTA). Since I enjoy problem solving, I have developed a special love for evidence synthesis and advanced health economic decision-modelling, using languages such as BUGS/JAGS and Stan coupled with R.

For some added personal bytes, I encourage the use of R for HTA. An extensive health economics R community has risen over the past several years. If any reader is interested, BCEA and DARTH are great R packages which have been specifically created for health economic decision-modelling. Also, R-HTA and DARTH are organisations which promote R and provide extensive tutorials on how to use the language for HTA. My own work includes the ongoing development of a sensitivity analysis framework for Lower and Middle-Income Country (LMIC) HTA analysts. A case study to support the framework can be found here. I am also a founding member of R-HTA in LMICs, a chapter of the main R-HTA consortium. The chapter aims to introduce and showcase the strengths of R programming to HTA analysts and health institutions in LMICs.

Joshua Soboil's Projects

advanced-r

Repository for worked through examples and exercises from Hadley Wickham's book 'Advanced R'

advent-of-code-2022

Advent of Code is an Advent calendar of small programming puzzles for a variety of skill sets and skill levels that can be solved in any programming language you like. People use them as interview prep, company training, university coursework, practice problems, a speed contest, or to challenge each other.

applied-predictive-modelling

Worked through chapters of Applied Predictive Modelling in R

bayesianmixturecure

bda_course_aalto

Bayesian Data Analysis course at Aalto

bookofr

The Book of R! by Tilman M. Davies.

chemotherapy_book

The model structure for the Chemotherapy example in the book "Value of Information for Health Economic Evalulations", Heath, Kunst and Jackson (2021)

cv

CV project code

dissertation

Code repository for "A Sensitivity Analysis Framework for Health Economic Evaluation in Middle Income Countries: Appropriately Incorporating a Comprehensive Approach"

doing-bayesian-data-analysis-2nd-ed.

Worked through exercises from the book "Doing Bayesian Data Analysis, 2nd Ed." by John Kruschke | 2015

evidence-synthesis-in-medical-decision-making

Replicated code and exercises from 'Evidence Synthesis for Decision Making in Healthcare', Welton J., et al. 2012

hands-on-programming-with-r-grolemund

Worked through textbook by Garrett Grolemund

hta-in-r-workshop-2020

Demonstration code used in the workshop.

introduction-to-bayesian-data-analysis

An introductory Youtube tutorial to Bayesian Inference | by Rasmus Bååth

introduction-to-statistical-learning

jsoboil

A little bit about me

jsoboil.github.io

Personal website of jSoboil

mastering-shiny

Completed exercises

microsimulation-tutorial

Code of the Microsimulation tutorial

multinma

Network meta-analysis of individual and aggregate data in Stan

network-meta-analysis-for-decision-making

Walk through and exercise scripts from 'Network Meta-Analysis for Decision-Making' by Dias S., et al. 2018

pdsh

Worked through examples and exercises from Jake VanderPlas' "Python Data Science Handbook"

r-for-data-science

R4DS | 2016

raos

Regression and Other Stories

stan

Getting started with Stan

stan-tutorials

Code for various Stan (mc-stan.org) tutorials.

statistical-computing-with-r

Worked through lessons and exercises from M. Rizzo's 'Statistical Computing with R', 2nd Ed.

statistical-rethinking

Worked through chapters and exercises from R. McElreath's 'Statistical Rethinking' textbook

survhe

Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.

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Some Bytes About Me:

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