Spearman Correlations of Symptoms and Patient-Reported Outcomes

Spearman correlations between the number of symptoms and patient-reported outcome measures, provided by author Xiaowu Sun and last updated in March 2026. The dataset is a 5.5 KB Excel file containing correlation coefficients for clinical research analysis.

Use Cases

• Calculate Spearman correlation coefficients between the number of symptoms and specific Patient-Reported Outcome Measures to assess symptom burden impact.
• Analyze the strength and direction of correlations for different symptom counts across various outcome measure categories.
• Validate clinical assessment tools by examining the relationship between symptom severity metrics and patient-reported scores.

Strengths

• Data is licensed under CC BY 4.0, facilitating open reuse and sharing.
• Focuses on Spearman correlation, a non-parametric measure suitable for ordinal data like symptom counts and patient-reported outcomes.
• Updated recently in March 2026, indicating current relevance.

Limitations

• Very small scale at 5.5 KB, suggesting a limited number of correlation pairs or a summary table rather than raw patient-level data.
• Unknown row and column counts prevent assessment of dataset scope and feature diversity.
• Lacks sample data and column definitions, making it difficult to evaluate structure and specific variables analyzed.

Provenance

Source

figshare

Collection Method

Analysis calculating Spearman correlations between symptom counts and patient-reported outcome measures.

Time Range

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Freshness

Last updated 2026-03-25.

Geography

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