arXiv (All)
open access
Optimal monotone conditional error functions
This paper presents a general method that provides optimal monotone conditional error functions for confirmatory adaptive two-stage designs with conditional power based sample size recalculations. The presented method builds on a previously developed general theory for optimal adaptive two-stage des
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Improving the Quality of Multiple Myeloma Treatment With Patient Care Plans#886812
- Disturbance Rejection Control under Nested Signal Temporal Logic Specifications: A Recursive Design Approach#987682
- The Cost Effectiveness of Treatment Strategies for Depression in Ethiopia: A Multiple Cohort Markov Model Analysis.#480787
- The Cost Effectiveness of Treatment Strategies for Depression in Ethiopia: A Multiple Cohort Markov Model Analysis#477472
- An optimal two-step estimation approach for two-phase studies#1049688
Record · ID 986083
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive