Jacobs Journal of Biostatistics

Jacobs Journal of Biostatistics: Upcoming Issue : December 2018 : For Submissions Contact at : submissions@jacobspublishers.com

SCOPE OF THE JOURNAL
Journal of Biostatistics Jacobs Journal of Biostatistics is a leading peer reviewed journal, promoting open access publishing in the collection of major scientific journals available in the scientific society. This promotes the application of statistical methods to the solution of biological problems. Bio-statistics is integral to the advance of knowledge in biology, health policy, clinical medicine, public health policy, health economics, proteomics, genomics, and other disciplines. Bio-statistics is particularly concerned with disentangling these different sources of variation.

Jacobs Journal of Biostatistics seeks to publish new bio statistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semi parametric methods. The journal publishes scientific work in the form of articles such as original articles, review articles, case reports, short communications etc.

Classification:

  • Prediction
  • Biomarker Evaluation
  • Survival Analysis
  • High Dimensional Data Analysis
  • Semi-parametric Method
  • Latent Class Models
  • Complex Sampling
  • Truncation
  • Survival Analysis
  • Array Comparative
  • Genomic Hybridization
  • Penalized likelihood models
  • Computational statistics
  • Genetic data
  • Epidemic Modeling
  • Spatial and Spatiotemporal Statistics
  • Bayesian Inference
  • Statistical Computing
  • Time Series Analysis
  • Modeling Diagnostics
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Editor-in-Chief

Dr. Haris Kokotas

Dr. Haris Kokotas
Institute of Child Health,
Athens, Greece

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JOURNAL HIGHLIGHTS

  • Prediction
  • Biomarker Evaluation
  • Survival Analysis
  • High Dimensional Data Analysis
  • Semi-parametric Method
  • Latent Class Models
  • Complex Sampling
  • Truncation
  • Survival Analysis
  • Array Comparative
  • Genomic Hybridization
  • Penalized likelihood models
  • Computational statistics
  • Genetic data
  • Epidemic Modeling
  • Spatial and Spatiotemporal Statistics
  • Bayesian Inference
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