The International Journal of Biostatistics
De Gruyter
About the journal
The International Journal of Biostatistics is a journal published by De Gruyter in Germany. It is listed in MEDLINE and PUBMED according to the sources read. Facts are reproduced as recorded at their sources with their capture dates; PublishLens indicators are available after sign-in.
Basic facts
- Publisher
- De Gruyter
- ISSN
- 2194-573X · 1557-4679
- Country
- Germany
- Access
- Not open access / not declared
Index listings
- MEDLINE · 2005-01-01
- PUBMED · 2008-01-17
- Indexing
- MEDLINE · PUBMED
- APC
- —
- Declared review time (DOAJ)
- —
- Actual review time (measured)
- 301 days received→accepted — computed from PubMed (n=60)
- Activity (OpenAlex)
- Active — latest works 2026
- PublishLens list status
- Shown after sign-in
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Methodology signals (dated facts from their sources)
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Descriptive metadata from public sources (DOAJ, OpenAlex, PubMed) as of the capture date shown — contains no assessment or judgment.
Works in OpenAlex
577
Last recorded publication year
2025
h-index
59
i10-index
226
From OpenAlex open data (CC0).
Editorial & policy5
- Observed digital preservation (Keepers registry)— snapshot 2026-10-05
- CLOCKSSPortico
- Norwegian register (HK-dir)— 2026
- Level 1 — approved scholarly channel
- Open references deposited at Crossref
- 91%
- ORCID iDs in current deposits
- 40%
- Enrolled in Crossref Similarity Check
- ✓
- Deposits licence metadata at Crossref
- ✓
Identity & continuity3
- Alternate titles
- The international journal of biostatics (Internet
- Source type
- journal
- NLM unique ID (PubMed)
- 101313850
Classification(no data)
No data available to the platform for this group
No platform data for: Classification — absence is not a judgment about the journal.
Subject areas
- Statistical Methods and Inference
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Statistical Methods and Bayesian Inference
- Advanced Causal Inference Techniques
- Advanced Causal Inference Techniques
- Statistical Methods in Clinical Trials
- Statistical Methods in Clinical Trials
Show all subjects (50)
- Bayesian Methods and Mixture Models
- Bayesian Methods and Mixture Models
- Advanced Statistical Methods and Models
- Health Systems, Economic Evaluations, Quality of Life
- Health Systems, Economic Evaluations, Quality of Life
- Advanced Statistical Methods and Models
- Optimal Experimental Design Methods
- Optimal Experimental Design Methods
- Gene expression and cancer classification
- Gene expression and cancer classification
- Genetic Associations and Epidemiology
- Bayesian Modeling and Causal Inference
- Statistical Distribution Estimation and Applications
- Genetic Associations and Epidemiology
- Bayesian Modeling and Causal Inference
- Statistical Distribution Estimation and Applications
- Genetic and phenotypic traits in livestock
- Genetic and phenotypic traits in livestock
- Reliability and Agreement in Measurement
- Reliability and Agreement in Measurement
- Bioinformatics and Genomic Networks
- Bioinformatics and Genomic Networks
- Insurance, Mortality, Demography, Risk Management
- Insurance, Mortality, Demography, Risk Management
- Genetic Mapping and Diversity in Plants and Animals
- Meta-analysis and systematic reviews
- Genetic Mapping and Diversity in Plants and Animals
- Meta-analysis and systematic reviews
- Liver Disease Diagnosis and Treatment
- Liver Disease Diagnosis and Treatment
- Hemodynamic Monitoring and Therapy
- Hemodynamic Monitoring and Therapy
- Data-Driven Disease Surveillance
- Data-Driven Disease Surveillance
- COVID-19 epidemiological studies
- COVID-19 epidemiological studies
- Financial Risk and Volatility Modeling
- Advanced Statistical Process Monitoring
- Advanced Statistical Process Monitoring
- Financial Risk and Volatility Modeling
- Computational Drug Discovery Methods
- Computational Drug Discovery Methods
Community confirmations — what users saw in MJL or Scopus Sources; not platform verification and never part of any score.
The journal's record in other sources:Web of Science MJLDOAJ