ENBIS-23 Valencia Conference

Session

INVITED Biostatistics

11 Sept 2023, 11:00

2.9/2.10

Conveners

INVITED Biostatistics

• Anne Gégout-Petit (Université de Lorraine)

6. Bayesian Spatial Modeling for Misaligned Data Fusion

Paula Moraga (King Abdullah University of Science and Technology (KAUST))

11/09/2023, 11:00

Other/special session/invited session

Spatially misaligned data are becoming increasingly common in fields such as epidemiology, ecology and the environment due to advances in data collection and management. Here, we present a Bayesian geostatistical model for the combination of data obtained at different spatial resolutions. The model assumes that underlying all observations, there is a spatially continuous variable that can be...

3. Design and Inference in a RCT when Treatment Observations Follow a Two-Component Mixture Model

Daniel Jeske (University of California, Riverside)

11/09/2023, 11:30

Other/special session/invited session

A mixture of a distribution of responses from untreated patients and a shift of that distribution is a useful model for the responses from a group of treated patients. The mixture model accounts for the fact that not all the patients in the treated group will respond to the treatment and their responses follow the same distribution as the responses from untreated patients. The treatment effect...

93. Accelerated Stability Study with SestakBerggren R Package: Impact of Statistics for Quicker Access to New Vaccines

Bernard Francq (GSK), Dr Olivier Schmit (GSK)

11/09/2023, 12:00

Biostatistics

The recent pandemic surged the emergency for quick access to new drugs and vaccines for the patients. Stability assessment of the product may represent a bottleneck when it is based on real-time data covering 2 or 3 years. To accelerate the decisions and ultimately the time-to-market, accelerated stability studies may be used with data obtained for 6 months. We show that the kinetic Arrhenius...

5. An Alternative to Statistical Process Control with Application to Healthcare Data

Benjamin Taylor (University College Cork)

Other/special session/invited session

Statistical process control (SPC) methods are applied across businesses in the monitoring of key performance indicators. These indicators often take the form of multiple univariate time series, each of which measures the `health' of some aspect of the business. SPC methods monitor these time series by highlighting unusual variation, changes in the mean, or local trends. Initially developed in...