International Journal of Health Statistics

International Journal of Health Statistics

International Journal of Health Statistics – Editor Resources

Open Access & Peer-Reviewed

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Editor Resources

Tools and guidance for consistent editorial decisions.

Editorial Resources

Resources help editors deliver timely, transparent, and rigorous decisions.

The editorial office is available for complex cases.

40%Max Fee Discount
3Free Publications
48hrPriority Review
500+Global Members

Resources Overview

Editors have access to reviewer selection tools, decision templates, and policy updates.

Resources include reviewer selection guidance, decision templates, and policy updates.

We encourage authors to document assumptions and sensitivity analyses so conclusions remain robust across populations.

Explain how missing data were handled and why chosen strategies were appropriate for the study design.

Report software versions and packages to support reproducibility across analytic environments.

Use tables and figures to communicate effect sizes, uncertainty, and subgroup comparisons clearly.

Training and Support

Training materials cover ethics, bias management, and statistical reporting expectations.

Training covers ethics, bias management, and transparent reporting expectations.

Transparent reporting of data provenance and governance supports reproducibility and ethical compliance in health statistics.

When presenting predictive models, report calibration, discrimination, and decision curve metrics where relevant.

When combining datasets, document linkage procedures and quality checks for matching accuracy.

If external validation is performed, describe population differences and implications for generalizability.

What You Receive

Decision Templates

Structured language for consistent editorial decisions.

Reviewer Guidance

Tools for matching manuscripts with expertise.

Policy Updates

Ethics and integrity updates for consistent handling.

Support is available for complex cases and appeals.

Well structured manuscripts accelerate peer review and help readers apply statistical insights to real world health decisions.

Define statistical terminology clearly for multidisciplinary readers who apply methods in clinical settings.

Highlight ethical safeguards for patient privacy, especially when working with linked or sensitive datasets.

Describe any model tuning or hyperparameter selection to support reproducibility in machine learning workflows.

Support Path

1

Access

Receive resource links during onboarding.

2

Apply

Use templates and guidance for each decision.

3

Consult

Seek editorial support for complex cases.

4

Update

Review policy updates on a regular cycle.

Clear statistical reporting improves the interpretability of health evidence for clinicians, policymakers, and research funders.

Provide uncertainty measures such as confidence intervals or credible intervals for key estimates and model outputs.

Summaries that connect statistical findings to health outcomes improve translation to policy and practice.

Include brief rationale for study design choices to support reviewer understanding and methodological transparency.

If data access is restricted, describe the approval process for qualified researchers and expected timelines.

Access Editor Resources

Stay supported throughout the editorial process.