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DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

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41 to 50 of 73,729 Results
MI for data with two censored covariates update.R
May 12, 2026 - Replication Data for: Analysis of Competing Risks Data with Covariates Subject to Detection Limits
R Syntax - 2.2 KB - MD5: acd5236e52c6aef963d0d542bfe66771
readme.docx
May 12, 2026 - Replication Data for: Analysis of Competing Risks Data with Covariates Subject to Detection Limits
MS Word - 12.5 KB - MD5: c0f34a70b1ba736dd0a0da02c74742a4
Documentation
simulate data with two censored covariates.csv
May 12, 2026 - Replication Data for: Analysis of Competing Risks Data with Covariates Subject to Detection Limits
Comma Separated Values - 25.1 KB - MD5: c63398e92dd9008631286b4b9d93014c
Mcode_direct likelihood approach.m
May 12, 2026 - Replication Data for: Regression analysis of interval-censored competing risks data with missing causes of failure: a direct likelihood approach
MATLAB Source Code - 6.2 KB - MD5: 8b35e79205a9ab973da77bce7db1d767
README.md
May 12, 2026 - Replication Data for: Regression analysis of interval-censored competing risks data with missing causes of failure: a direct likelihood approach
Markdown Text - 708 B - MD5: 51f4fc03aad7e023695b95094d14639d
Documentation
Mcode.m
May 12, 2026 - Replication Data for: Flexible modeling of left-truncated and interval-censored competing risks data with missing event types
MATLAB Source Code - 6.4 KB - MD5: cb4af006e4ed61c6477494bcb30ee23e
CalCopula.R
May 12, 2026 - Replication Data for: Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis
R Syntax - 10.2 KB - MD5: e3e47645df658dd02c145288c49ce9d9
CalRunTime.R
May 12, 2026 - Replication Data for: Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis
R Syntax - 5.1 KB - MD5: c7ddbc1e8eca147f7e4c77964aa6f9d0
clayton_divergence_recovery.R
May 12, 2026 - Replication Data for: Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis
R Syntax - 18.0 KB - MD5: c5cf9dc20c5349f052417c72a16013aa
framinghan_calibration_cens.R
May 12, 2026 - Replication Data for: Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis
R Syntax - 2.7 KB - MD5: b8b399c1febf10e671a1f2def1f6632e
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