| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 211 | 37 | 51 | 12 |
The journal focuses on Statistics, Econometrics, Covariate, Artificial intelligence and Estimator. Statistics and Inference are closely related fields of research discussed in Biostatistics. The study on Inference presented in it intersects with subjects under the field of Data mining.
It focused on Data mining research but expanded to cover Cluster analysis. In the journal, Outcome (probability), Proportional hazards model, Missing data and Random effects model are investigated in conjunction with one another to address concerns in Econometrics research. Topics in Artificial intelligence were tackled in line with various other fields like Machine learning and Pattern recognition.
The journal covers various topics on Bayesian probability such as Bayes' theorem, Bayesian inference and Markov chain Monte Carlo.
The journal papers focus on Statistics, Econometrics, Data mining, Bayesian probability and Covariate. The most cited papers address concerns in the field of Econometrics by exploring it in line with topics in Markov chain Monte Carlo which intersect with Markov chain and Multivariate statistics subjects. The most cited articles explore issues in Data mining which can be linked to other research areas like Normalization (statistics), Parametric statistics, Inference and Gene chip analysis, DNA microarray.
The main points discussed in the journal deals with Statistics, Artificial intelligence, Inference, Bayesian probability and Covariate. It explores topics in Artificial intelligence which can be helpful for research in disciplines like Functional magnetic resonance imaging, Breast cancer, False discovery rate, Machine learning and Pattern recognition. The featured Machine learning studies mainly concentrate on Bayes' theorem but also cover areas of interest in Algorithm.
It explores research in Inference alongside concepts in Econometrics and other areas of study in Random effects model. The presented Covariate research focuses mostly on Linear regression and, on occasion, topics in Sample size determination. The research on Feature selection tackled can also make contributions to studies in the areas of Regression analysis, Count data and Data mining.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Biostatistics (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Biostatistics (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 9.71% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 39.78% were posted by at least one author from the top 10 institutions publishing in the journal. Another 20.43% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.35% of all publications and 20.43% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Ruitao Lin;Ying Yuan
(2020)Theresa Stocks;Tom Britton;Michael Höhle
(2020)Matthew A Psioda;Jiawei Xu;Qi Jiang;Chunlei Ke
(2021)Katie Wilson;Jon Wakefield
(2020)Ruilin Li;Christopher Chang;Johanne M Justesen;Yosuke Tanigawa
(2020)Magnus M Münch;Carel F W Peeters;Aad W Van Der Vaart;Mark A Van De Wiel
(2021)Kathrin Möllenhoff;Florence Loingeville;Julie Bertrand;Thu Thuy Nguyen
(2020)Weichi Yao;Halina Frydman;Jeffrey S Simonoff
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