We review Bayesian and Bayesian decision theoretic approaches to subgroup analysis and applications to subgroup-based adaptive clinical trial designs. Subgroup analysis refers to inference about ...
Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...
Journal of Agricultural, Biological, and Environmental Statistics, Vol. 20, No. 4 (December 2015), pp. 555-576 (22 pages) RNA-sequencing (RNA-seq) technologies have revolutionized the way that ...
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 36, No. 1 (Mar., 2008), pp. 5-21 (17 pages) The authors extend the classical Cormack-Jolly-Seber mark-recapture model to ...
In the Big Data era, many scientific and engineering domains are producing massive data streams, with petabyte and exabyte scales becoming increasingly common. Besides the explosive growth in volume, ...
A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...
Scientists have developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. Bayesian statistics has been in the spotlight in recent years due to ...
Here’s our estimate of public support for vouchers, broken down by religion/ethnicity, income, and state: (Click on image to see larger version.) We’re mapping estimates from a hierarchical Bayes ...
Read more to learn how headache disorders continue to affect billions worldwide and why improved prevention strategies are ...
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