Bayesian methods are supporting decisions and news at the national level!

The Centers for Disease Control and Prevention summarizes a report published in the journal Population Health Metrics. The news also made it to the national media. The report (JP Boyle, TJ Thompson, EW Gregg, LE Barker, and DF Williamson (2010) “Projection of the year 2050 burden of diabetes in the US adult population: dynamic modeling of incidence, mortality, and prediabetes prevalence.”*Population Health Metrics*. 8:29) projects a two fold increase in the annual incidence of diabetes among American adults. The authors project the prevalence of diabetes to increase from 14% to between 25% and 28% by 2050. However, the authors claim that “these projected increases are largely attributable to the aging of the US population, increasing numbers of members of higher-risk minority groups in the population, and people with diabetes living longer.”

The authors model the incidence of diabetes at year according to the Bayesian nonlinear model:

where

is a logistic function of time with asymptote

. The parameters

and

were given diffuse normal priors, and

was modeled using a variety of autoregressive strategies. The authors use

WinBUGS for posterior summary, also citing

*Bayesian Data Analysis* by Gelman

*et al.* (2004).

*Related*

To

**leave a comment** for the author, please follow the link and comment on their blog:

** BioStatMatt » R**.

R-bloggers.com offers

**daily e-mail updates** about

R news and

tutorials on topics such as:

Data science,

Big Data, R jobs, visualization (

ggplot2,

Boxplots,

maps,

animation), programming (

RStudio,

Sweave,

LaTeX,

SQL,

Eclipse,

git,

hadoop,

Web Scraping) statistics (

regression,

PCA,

time series,

trading) and more...

If you got this far, why not

__subscribe for updates__ from the site? Choose your flavor:

e-mail,

twitter,

RSS, or

facebook...

**Tags:** Bayesian, health, R, statistics, Technical