Project
This page borrows the cohort-taxonomy logic from your small-sample methods work and applies it to CT.gov: not effect heterogeneity, but visibility heterogeneity by recorded trial scale.
Small registered studies remain far quieter than larger trials, but size does not fully rescue the biggest sponsor-class backlogs.
A standalone E156 project on how enrollment size maps onto older-study visibility, ghost protocols, and sponsor-class contrasts.
Across The Series
The split projects are meant to be read together because each isolates a different dimension of registry opacity rather than forcing every question into one leaderboard.
Industry-focused missing-results stock, sponsor backlogs, and structural sparsity inside CT.gov.
Sponsor-class comparisons on rate, stock, and structural hiddenness rather than one flattened ranking.
Phase-by-phase disclosure gaps showing how silence changes along the development pathway.
Field-level missingness across publication links, IPD statements, descriptions, and locations.
Results-plus-publication visibility states showing how many older trials are fully visible, partly visible, or ghosted.
Completion-era reporting debt showing how older eligible cohorts drift on no-results and ghost-protocol rates.
Keyword-classified therapeutic-area hiddenness mapping across common condition families.
Concentration and inequality analysis showing how much unresolved stock sits inside a thin sponsor slice.
Policy-era comparisons across pre-FDAAA, FDAAA, and later CT.gov completion cohorts.
Sample-based external PubMed NCT audit testing how often CT.gov no-link records hide an external paper trail.
Oncology-specific CT.gov hiddenness showing where cancer-trial stock, phases, and sponsors still go quiet.
Cardiovascular CT.gov hiddenness showing how heart and vascular studies remain quiet across major phases and sponsors.
Metabolic CT.gov hiddenness across obesity, diabetes, and related trial portfolios with large late-phase and NA stock.
Site and country footprint analysis showing how larger trial geographies map onto much better public visibility.
Primary-purpose and allocation analysis showing which trial intents remain most obscured on CT.gov.
Registration-to-completion delay analysis showing short-cycle studies carry the heaviest reporting debt.
Arm-count and intervention-count analysis showing simpler trial architectures are often the quietest.