Multiple Sclerosis Cognitive Risk Models with Hierarchical Logistic Regression

A 9.5 KB Excel file containing hierarchical logistic regression models investigating the association between covariates and cognitive domains with conversion risk status. The dataset was authored by Omid Mirmosayyeb and last updated on March 20, 2026. It is licensed under CC-BY-4.0 and shared on the figshare platform.

Use Cases

• Predicting conversion to high-risk status in multiple sclerosis patients based on cognitive domain scores.
• Investigating pairwise correlations between clinical covariates and cognitive test results.
• Building risk stratification models for routine clinical practice in neurology.

Strengths

• Dataset is small (9.5 KB), facilitating quick download and inspection.
• Models are explicitly described as hierarchical logistic regression, providing a clear analytical framework.
• License is permissive (CC-BY-4.0), allowing for reuse and modification.

Limitations

• Row count and column definitions are unknown, requiring manual inspection after download.
• Description metadata is limited; actual data quality requires manual inspection after download.
• The dataset's small size suggests it contains model outputs or summary statistics, not raw patient-level data.

Provenance

Source

figshare, author Omid Mirmosayyeb

Collection Method

Likely contains statistical model outputs from a clinical study.

Time Range

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Freshness

Last updated 2026-03-20 17:27:16; freshness should be verified.

Geography

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