International Journal of Biostatistics
期刊基本信息
期刊名称:International Journal of Biostatistics
出版国家或地区:UNITED STATES
是否OA:No
期刊ISSN:2194-573X
涉及的研究方向:MATHEMATICAL & COMPUTATIONAL BIOLOGY-STATISTICS &
期刊数据表:
最新中科院JCR分区
|
大类(学科)
小类(学科)
JCR学科排名
数学
MATHEMATICAL & COMPUTATIONAL BIOLOGY(数学和计算生物学) 4区
STATISTICS & PROBABILITY(统计学和概率) 4区
51/59
76/123
|
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最新的影响因子
|
0.676 | |||||||
最新公布的期刊年发文量 |
|
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总被引频次 | 517 | |||||||
特征因子 | 0.001550 |
International Journal of Biostatistics英文简介:
The International Journal of Biostatistics (IJB) seeks to publish new biostatistical 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 semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.
International Journal of Biostatistics中文简介:
国际生物统计学杂志(IJB)致力于发表新的生物统计模型和方法,新的统计理论,以及统计方法的原始应用,以解决生物学、医学、公共卫生和农业科学中出现的重要实际问题,重点是半参数方法。鉴于许多替代发布存在于生物统计学,IJB发布提供了一个研究生物统计学关注现代方法,通常基于机器学习和其他data-adaptive方法,以及提供一个独特的阅读体验,迫使作者明确的统计推断问题解决的。IJB的目的是使该杂志涵盖生物统计学的全部范围,从理论进展到将实际问题的相关和合理翻译成统计框架。电子出版物还允许附加数据和软件代码,并为可重复研究打开了大门,使读者可以轻松地复制论文中描述的分析。我们将欢迎原创的研究和评论文章,以及将健全的统计方法应用于实际问题的文章。
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