This is a general collection of COVID-19 data deposited in the Harvard Dataverse repository. The list in this collection is maintained by the Harvard Dataverse data curation team (IQSS and Harvard Library). Researchers who deposit their related data into Harvard Dataverse will have their data linked to this collection, to increase discoverability of their data. Please use the contact link if you have any questions about this collection.
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71 to 80 of 58,531 Results
Replication Data for: Partisanship Unmasked? The Role of Politics and Social Norms in COVID-19 Mask-Wearing Behavior
May 6, 2025 - Journal of Experimental Political Science
Carey, John; Nyhan, Brendan; Phillips, Joseph; Reifler, Jason, 2022, "Replication Data for: Partisanship Unmasked? The Role of Politics and Social Norms in COVID-19 Mask-Wearing Behavior", https://doi.org/10.7910/DVN/PJ27BB, Harvard Dataverse, V2, UNF:6:KSDyLTJNZVToKO4x/KWjgQ== [fileUNF]
Replication data for both the main analysis and power analyses.
Updated Regression Analyses.R
May 6, 2025 - Replication Data for: Partisanship Unmasked? The Role of Politics and Social Norms in COVID-19 Mask-Wearing Behavior
R Syntax - 111.8 KB - MD5: b1fcc1f16e0eedfb48de3d3fd306942b
Replication Data for: Specific Biomarkers Differentiate Cerebral Malaria from Other Causes of Coma in African children
May 6, 2025 - Biosciences Dataverse
Mwangi, Shaban; Gomes, Claudia; Abdi, Abdirahman, 2025, "Replication Data for: Specific Biomarkers Differentiate Cerebral Malaria from Other Causes of Coma in African children", https://doi.org/10.7910/DVN/7IKHOR, Harvard Dataverse, V1, UNF:6:KLAMdC6vofVKSpF4BYxeAA== [fileUNF]
This is a replication dataset for the manuscript titled: "Specific Biomarkers Differentiate Cerebral Malaria from Other Causes of Coma in African children" The dataset file contains study participants' clinical characteristics and measurements as well as measured/quantified ELISA analytes.
Specific_biomarkers_for_CM_final_patient_data_anon.tab
May 6, 2025 - Replication Data for: Specific Biomarkers Differentiate Cerebral Malaria from Other Causes of Coma in African children
Tabular Data - 46.3 KB - 29 Variables, 380 Observations - UNF:6:KLAMdC6vofVKSpF4BYxeAA==
csv fileData
Specific_biomarkers_for_CM_final_patient_data_Readme.txt
May 6, 2025 - Replication Data for: Specific Biomarkers Differentiate Cerebral Malaria from Other Causes of Coma in African children
Plain Text - 5.3 KB - MD5: 03acba118e83fbfd7fa8cd80ef639192
DocumentationReadme
Building the Evidence Base for Health System Transformation Through Designing and Testing of Future Health System Models and Measure: PNC Data
May 6, 2025 - Health Economics Research Unit (HERU) Dataverse
Mugenya, Irene; Mbogori, Maurice Murugu; Oluoch, Dorothy; Amboko, Beatrice; Kosgei, Rose J.; Karimi, Janette; Nzinga, Jacinta, 2025, "Building the Evidence Base for Health System Transformation Through Designing and Testing of Future Health System Models and Measure: PNC Data", https://doi.org/10.7910/DVN/2P8DPM, Harvard Dataverse, V1, UNF:6:NZp9At7rhRTvhWYDWOU7Ow== [fileUNF]
Quality postnatal care (PNC) is crucial for safeguarding the health of both the mother and her newborn through effective screening, timely identification of complications, and adequate education on self-care and infant care. Timely interventions during this period have been shown to improve maternal and neonatal outcomes. However, evidence indicate...
DATA_CODEBOOK E cohort.docx
May 6, 2025 - Building the Evidence Base for Health System Transformation Through Designing and Testing of Future Health System Models and Measure: PNC Data
MS Word - 34.7 KB - MD5: d808e44c3ea0679886370f1bf40d1370
Documentation
Data_Readme E cohort.txt
May 6, 2025 - Building the Evidence Base for Health System Transformation Through Designing and Testing of Future Health System Models and Measure: PNC Data
Plain Text - 4.2 KB - MD5: 41069e7d0c5e9830e6014d530047865f
Documentation
PNCdataset.tab
May 6, 2025 - Building the Evidence Base for Health System Transformation Through Designing and Testing of Future Health System Models and Measure: PNC Data
Tabular Data - 181.6 KB - 68 Variables, 792 Observations - UNF:6:NZp9At7rhRTvhWYDWOU7Ow==
Data
SPIRIT 2013 Checklist: Hydroxyurea - Pragmatic Reduction In Mortality and Economic burden (H-PRIME): A 2x2x2 factorial randomised open-label trial investigating practical approaches to the treatment of sickle cell disease at four sites in Eastern Uganda: ISRCTN 15724013
May 2, 2025 - Human Genetic Factors (HGF) Group
Williams, Tom, 2025, "SPIRIT 2013 Checklist: Hydroxyurea - Pragmatic Reduction In Mortality and Economic burden (H-PRIME): A 2x2x2 factorial randomised open-label trial investigating practical approaches to the treatment of sickle cell disease at four sites in Eastern Uganda: ISRCTN 15724013", https://doi.org/10.7910/DVN/QUGG6P, Harvard Dataverse, V3
Package includes a SPIRIT checklist and Trial assessment schedule. Trial Registration Number: ISRCTN 15724013
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