Biostatistics deals with data arising from biomedical research. It remains a very active research area with complicated time-to-event data and missing data emerging in application areas including medicine, genetics, neuroscience, and engineering. Recent advances in biomedical research have created new challenges and opportunities for statistics researchers and data scientists. For example, big data analysis, precision medicine, artificial intelligence, causal inference, and other new research fields have inspired data scientists to develop modern statistical methods and innovative inference procedures. This special issue aims to provide a forum for researchers to present new methods and novel applications motivated by biomedical examples in the broad areas of contemporary biostatistics. Authors are invited to submit original research and review articles that will stimulate interest in contemporary biostatistics.

Potential topics include but are not limited to the following:

• Missing data analysis
• Precision medicine
• Clinical trials
• Causal inference
• Longitudinal data analysis
• Survival analysis
• High dimensional data analysis and big data analysis
• fMRI data analysis
• Health care data analysis
• Neuroscience data analysis
• Functional data analysis