Missing Value Proportions for Variables in a Carotid Artery Meta-Analysis

Supplementary Material 6 provides a breakdown of missing data proportions for each variable in a pooled dataset. The 5.7 KB XLSX file, authored by Anand Ruban Agarvas and last updated on 2026-04-28, supports a machine-learning informed meta-analysis investigating ferritin and transferrin as predictors of carotid artery thickness in females. It was released under a CC-BY-4.0 license on figshare.

Use Cases

• Assess data completeness for statistical modeling based on the reported missing value proportions.
• Inform imputation strategy selection for clinical variables based on the extent of missingness.
• Evaluate potential bias in a pooled meta-analysis dataset based on variable-level missing data.
• Plan data cleaning workflows for cardiovascular research datasets based on missing data metrics.

Strengths

• Provides specific missing value proportions for each variable, a key metric for data quality assessment.
• Released under a permissive CC-BY-4.0 license, facilitating reuse.
• Directly supports a published machine-learning informed meta-analysis, indicating research relevance.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.

Provenance

Source

figshare, as supplementary material for a research publication.

Collection Method

Likely derived from the pooled individual participant data used in the referenced meta-analysis.

Time Range

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Freshness

Last updated 2026-04-28 04:02:36; freshness should be verified.

Geography

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