Mahmood Ahmad
Tahir Heart Institute
author@example.com

Protocol: CT.gov Structural Missingness

This protocol quantifies field-level structural missingness across the March 29, 2026 ClinicalTrials.gov full-registry snapshot. The full 578,109-study universe is used to estimate missingness in publication links, IPD statements, detailed descriptions, locations, and outcome fields. Secondary outputs compare structural sparsity across sponsor classes so descriptive loss is not mistaken for a uniform registry problem. The project is designed to surface information loss that occurs even when results-reporting rules are not the direct analytic target.

Outside Notes

Type: protocol
Primary estimand: Field-level structural missingness across the full registry
App: CT.gov Structural Missingness dashboard
Code: https://github.com/mahmood726-cyber/ctgov-structural-missingness
Date: 2026-03-29
Validation: FULL REGISTRY RUN

References

1. ClinicalTrials.gov API v2. National Library of Medicine. Accessed March 29, 2026.
2. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement. BMJ. 2021;372:n71.
3. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to Meta-Analysis. 2nd ed. Wiley; 2021.

AI Disclosure

This work represents a compiler-generated evidence micro-publication built from structured registry data and deterministic summary code. AI was used as a constrained coding and drafting assistant for interface generation, packaging, and prose refinement, not as an autonomous author. The analytical choices, interpretation, and final outputs were reviewed by the author, who takes responsibility for the content.