**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**30184

##### A Bayesian Hierarchical 13COBT to Correct Estimates Associated with a Delayed Gastric Emptying

**Authors:**
Leslie J.C.Bluck,
Sarah J.Jackson,
Georgios Vlasakakis,
Adrian Mander

**Abstract:**

The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.

**Keywords:**
Bayesian hierarchical analysis,
13COBT,
Gastricemptying,
WinBUGS.

**Digital Object Identifier (DOI):**
doi.org/10.5281/zenodo.1330995

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