1 to 10 of 2,378 Results
May 20, 2026 - COOK Alistair David Blair
COOK, Alistair David Blair, 2026, "RSIS HADR Database", https://doi.org/10.21979/N9/DXYVE7, DR-NTU (Data), V1
Description: A multi-phase research project that involves collecting and analysing data to study the actions, interactions, and transactions of key Humanitarian Assistance and Disaster Relief (HADR) actors in Southeast Asia and wider Asia-Pacific. Purpose: To explore the ways sta... |
May 19, 2026 - Michael STANLEY-BAKER
Stanley-Baker, Michael, 2026, "Count Data for Sui Jingji zhi 隋經籍志, Hanshu Yiwen zhi 漢書藝文誌 and Bianzheng lun 辯正論", https://doi.org/10.21979/N9/MVPBRH, DR-NTU (Data), V2, UNF:6:qHIwT1Q3h1MPKit7FE/olg== [fileUNF]
Count of titles in two imperial bibliographies and a Daoist Catalogue. Statistical evidence for distribution of knowledge types in the three works. |
May 15, 2026 - TAN Elaine Hui Zhi
Tan, Elaine Hui Zhi, 2028, "Replication Data for: Tsunami Hazard Assessment for Singapore and the Sunda Shelf Region", https://doi.org/10.21979/N9/DCKJWW, DR-NTU (Data), V1
This dataset comprises the data files and model setup files used to generate the simulations presented in the thesis, Tsunami Hazard Assessment for Singapore and the Sunda Shelf Region, in support of the reproducibility of the research. |
May 14, 2026 - Jia Min LEE
Lee, Jia Min, 2026, "Replication data for: Physicochemical-informed predictive modelling on small datasets for designing conductive polymer inks in soft bioelectronics", https://doi.org/10.21979/N9/WC4D7J, DR-NTU (Data), V1, UNF:6:S0x4Y5WE079p7+0mwh5wgg== [fileUNF]
Dataset for physico surrogate model and |
May 13, 2026 - NIE Data Repository (Harvested)
Goodwill, Alicia Marie, 2026, "Caffeine and Physical performance in female intermittent sport athletes: a systematic review and meta-analysis considering menstrual cycle phase", https://doi.org/10.25340/R4/7HSLJO
Supporting dataThis Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Disease progression based feature screening for ultrahigh-dimensional survival-associated biomarkers", https://doi.org/10.21979/N9/OSRVWN, DR-NTU (Data), V1
This dataset contains the R code for simulation studies reported in the paper "Disease progression based feature screening for ultrahigh-dimensional survival-associated biomarkers". |
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Analysis of Competing Risks Data with Covariates Subject to Detection Limits", https://doi.org/10.21979/N9/NNUDA2, DR-NTU (Data), V1
This dataset contains a set of simulated data and the R code for simulation studies reported in the paper "Analysis of Competing Risks Data with Covariates Subject to Detection Limits". |
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Regression analysis of interval-censored competing risks data with missing causes of failure: a direct likelihood approach", https://doi.org/10.21979/N9/MPYZO1, DR-NTU (Data), V1
This dataset contains the MATLAB code used to generate the simulation results reported in the paper "Regression analysis of interval-censored competing risks data with missing causes of failure: a direct likelihood approach". |
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Flexible modeling of left-truncated and interval-censored competing risks data with missing event types", https://doi.org/10.21979/N9/HCO7AV, DR-NTU (Data), V1
This dataset contains the MATLAB code used to generate the simulation results reported in the paper "Flexible modeling of left-truncated and interval-censored competing risks data with missing event types". |
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis", https://doi.org/10.21979/N9/TQODZO, DR-NTU (Data), V1
This dataset contains simulation results and R code used to generate the results in the paper "Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis". |
