Statistics in Biosciences - h5 Index Rating

The h5-index is a product of Google Scholar and shows a journal’s h-Index based on the journal’s articles published in the last 5 calendar years (with an overall minimum of 100 articles published during these years). The variable h is defined as the largest number of articles that have each been cited h times. The h5-Index therefore cannot be dominated by one or a few highly cited articles. 

In 2020, Statistics in Biosciences received the following ratings:

h5-Index	h5-Median
11	22

Statistics in Biosciences highlights some of these top cited articles:

• Subgroup-Based Adaptive (SUBA) Designs for Multi-arm Biomarker Trials (this opens in a new tab)
  Y Xu, L Trippa, P Müller, Y Ji
  Statistics in Biosciences 8.1 (July 2014)
   

• On a Statistical Transmission Model in Analysis of the Early Phase of COVID-19 Outbreak. (this opens in a new tab)
  Y Zhu, YQ Chen
  Statistics in Biosciences 13.1 (April 2020)
   

• Understanding Landmarking and Its Relation with Time-Dependent Cox Regression (this opens in a new tab)
  H Putter, HC van Houwelingen
  Statistics in Biosciences 9.1 (July 2016)
   

• Quantifying Infinite-Dimensional Data: Functional Data Analysis in Action (this opens in a new tab)
  K Chen, X Zhang, A Petersen, HG Müller
  Statistics in Biosciences 9.2 (November 2015)
   

• Dynamic Prediction of Renal Failure Using Longitudinal Biomarkers in a Cohort Study of Chronic Kidney Disease (this opens in a new tab)
  L Li, S Luo, B Hu, T Greene
  Statistics in Biosciences 9.2 (November 2016)