MI-B: Multiple Imputation with B-Splines for Clinical Trial Monitoring

A methodological article and associated materials proposing a multiple imputation technique using B-splines for monitoring parameters in clinical trials. The work was authored by Minling Zhang and last updated on June 2, 2026. The dataset is small, consisting of 197.3 KB of supporting files in PDF, ZIP, and DOCX formats.

Use Cases

• Estimating premature study discontinuation rates based on covariate information mentioned in the description
• Simulating trial monitoring scenarios under varying functional forms of missingness as described
• Comparing imputation model robustness for clinical trial data as discussed in the article

Strengths

• Method is described as accurately and efficiently estimating targeted parameters in simulation studies.
• Files are provided in multiple common formats (PDF, ZIP, DOCX) for accessibility.
• Dataset is openly licensed under CC-BY-4.0.

Limitations

• The dataset is very small (197.3 KB), indicating limited scope or primarily documentation.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Likely contains simulation data and analysis supporting the proposed statistical method.

Freshness

Last updated 2026-06-02 14:24:08; freshness should be verified.