Enhanced Statistical Reporting Guidelines

Last Updated: January 4, 2025

The Advanced Journal of Biomedicine & Medicine (AJBM) requires rigorous and transparent statistical reporting to ensure reproducibility, research integrity, and reader confidence. These guidelines align with COPE recommendations, ICMJE standards, and international best practices for biomedical publishing.

1. Core Principles

1.1 Transparency

  • Full disclosure of all statistical methods.

  • Clear documentation of analytic choices.

  • Reporting of all planned outcomes, including negative results.

  • Data and code availability, where feasible.

1.2 Reproducibility

  • Comprehensive methodological detail for replication.

  • Version control for software and analysis scripts.

  • Availability of raw data, processed data, and protocols when ethically possible.

  • Clear documentation of preprocessing and transformations.

2. Study Design and Planning

2.1 Sample Size and Power

Authors must report:

  • Power or sample size calculations, including assumptions.

  • Effect size estimates.

  • Interim analysis or stopping rules (if applicable).

Example:
“Sample size was calculated using G*Power 3.1 with α=0.05, power=0.80, and effect size d=0.5, requiring 128 participants.”

2.2 Hypotheses

  • Primary and secondary hypotheses must be explicitly stated.

  • Directional vs. non-directional tests must be specified.

  • Adjustments for multiple comparisons should be described.

3. Data Analysis Requirements

3.1 Descriptive Statistics

Reports must include:

  • Mean ± SD for normally distributed data.

  • Median (IQR) for non-normal data.

  • Sample sizes (n) for all groups.

  • Missing data counts and handling methods.

  • Evidence of distribution assessment.

Example Table:

Variable Group A (n=50) Group B (n=50) p-value
Age 45.2 ± 8.4 46.1 ± 7.9 0.56
BMI 24.5 (22–27) 25.1 (23–28) 0.48

3.2 Inferential Statistics

Reports must include:

  • Justification of test selection.

  • Assumption checks and how violations were handled.

  • Effect sizes with 95% confidence intervals.

  • Exact p-values (e.g., p=0.032), unless p < 0.001.

4. Specific Analysis Guidelines

4.1 Regression Analyses

Authors must specify:

  • Model type and specification.

  • Variable selection procedures.

  • Assumption checks (linearity, multicollinearity, residuals).

  • Goodness-of-fit measures.

  • Parameter estimates with confidence intervals.

4.2 Survival Analyses

Reports must include:

  • Definition of censoring.

  • Method of survival time calculation.

  • Handling of competing risks.

  • Tests of proportional hazards.

5. Data Visualization Standards

5.1 Figures

  • Axes must be labeled clearly.

  • Error bars should represent SD or 95% CI, defined in legend.

  • Sample sizes indicated where appropriate.

  • Statistical significance annotations clearly explained.

5.2 Tables

  • Variables clearly defined.

  • Precision consistent and appropriate.

  • Missing data indicated.

  • Statistical test used identified in table notes.

6. Special Considerations

6.1 Missing Data

Authors must document:

  • Missing data patterns.

  • Handling methods (e.g., imputation, complete-case analysis).

  • Sensitivity analyses where applicable.

6.2 Multiple Testing

Authors must report:

  • Adjustments for multiple comparisons (e.g., Bonferroni, FDR).

  • Presentation of adjusted and unadjusted results.

  • Hierarchical or pre-specified testing procedures.

7. Reporting by Study Type

7.1 Randomized Controlled Trials (RCTs)

  • Must follow CONSORT guidelines.

  • Randomization methods and allocation concealment described.

  • Intention-to-treat analysis reported.

7.2 Observational Studies

  • Must follow STROBE guidelines.

  • Confounding assessment methods described.

  • Bias evaluation addressed.

  • Exposure–outcome modeling explained.

8. Quality Control

8.1 Data Quality

  • Data cleaning and validation procedures reported.

  • Outlier detection and handling explained.

8.2 Analysis Quality

  • Independent code review recommended.

  • Reproducibility checks documented.

  • Version control and software identifiers included.

9. Example Reporting

  • Sample Size: “For detecting a 5-unit mean difference (SD=10) with α=0.05 and power=0.80, 64 participants per group were required.”

  • Results: “Treatment effect = 5.2 units (95% CI: 3.1–7.3, p=0.002), adjusted for age and sex.”

10. Implementation Checklist

Pre-submission:
Statistical methods fully described.
All primary and secondary outcomes reported.
Effect sizes and CIs included.
Data availability statement provided.
Code availability documented.

Post-review:
Reviewer statistical concerns addressed.
Any additional analyses documented.
Revisions transparently reported.
Final results verified.

11. Ethical and Transparency Requirements

  • Data Privacy: Protection of participants’ confidentiality.

  • Informed Consent: Required for all human data.

  • Ethics Approval: Must be reported with IRB/committee details.

  • Protocol Registration: Required for clinical trials.

  • Deviations: Any departures from pre-specified analysis plans must be explained.