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Disrupted Data: Using Longitudinal Assessment Systems to Monitor Test Score Quality

• Authors : An, Lily Shiao; Ho, Andrew Dean; Davis, Laurie Laughlin

Subjects: Education; longitudinal analysis; longitudinal data

• Source: An, Lily S., Andrew D. Ho, and Laurie Laughlin Davis. 2022. Disrupted data: Using longitudinal assessment systems to monitor test score quality. Educational Measurement:

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Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems

• Authors : Clough, David R.; Wu, Andy

Subjects: Management of Technology and Innovation; Strategy and Management; General Business

• Source: Clough, David R., and Andy Wu. "Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems." Academy of Management Review 47,

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Application of data pooling to longitudinal studies of early post-traumatic stress disorder (PTSD): the International Consortium to Predict PTSD (ICPP) project

• Authors : Qi, Wei; Ratanatharathorn, Andrew; Gevonden, Martin

Subjects: PTSD; pooled analysis; data harmonization

• Source: Qi, W., A. Ratanatharathorn, M. Gevonden, R. Bryant, D. Delahanty, Y. Matsuoka, M. Olff, et al. 2018. “Application of data pooling to longitudinal studies of early

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DQe-v: A Database-Agnostic Framework for Exploring Variability in Electronic Health Record Data Across Time and Site Location

• Authors : Estiri, Hossein; Stephens, Kari

Subjects: Electronic Health Records; Data Quality; Data Variability

• Source: Estiri, Hossein, and Kari Stephens. 2018. “DQe-v: A Database-Agnostic Framework for Exploring Variability in Electronic Health Record Data Across Time and Site

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Robust joint score tests in the application of DNA methylation data analysis

• Authors : Li, Xuan; Fu, Yuejiao; Wang, Xiaogang

Subjects: Methylation data; Joint score tests; Variability

• Source: Li, Xuan, Yuejiao Fu, Xiaogang Wang, and Weiliang Qiu. 2018. “Robust joint score tests in the application of DNA methylation data analysis.” BMC Bioinformatics 19

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Evaluating Foundational Data Quality in the National Patient-Centered Clinical Research Network (PCORnet®)

• Authors : Qualls, Laura Goettinger; Phillips, Thomas A.; Hammill, Bradley G.

Subjects: electronic health records; quality improvement; patient-centered care

• Source: Qualls, Laura Goettinger, Thomas A. Phillips, Bradley G. Hammill, James Topping, Darcy M. Louzao, Jeffrey S. Brown, Lesley H. Curtis, and Keith Marsolo. 2018. “Evaluating Foundational

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Improving risk prediction accuracy for new soldiers in the U.S. Army by adding self-report survey data to administrative data

• Authors : Bernecker, Samantha; Nock, Matthew; Chiu, Wai

Subjects: Army; Military; Predictive modeling

• Source: Bernecker, S. L., A. J. Rosellini, M. K. Nock, W. T. Chiu, P. M. Gutierrez, I. Hwang, T. E. Joiner, et al. 2018. “Improving risk prediction accuracy for new soldiers in the U.S. Army by adding

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Big data and data repurposing - using existing data to answer new questions in vascular dementia research

• Authors : Doubal, Fergus N.; Ali, Myzoon; Batty, G. David

Subjects: Big data; Data; Clinical Trials

• Source: Doubal, F. N., M. Ali, G. D. Batty, A. Charidimou, M. Eriksdotter, M. Hofmann-Apitius, Y. Kim, et al. 2017. “Big data and data

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drLumi: An open-source package to manage data, calibrate, and conduct quality control of multiplex bead-based immunoassays data analysis

• Authors : Sanz, Hector; Aponte, John J.; Harezlak, Jaroslaw

Subjects: Mathematical and Statistical Techniques; Mathematical Functions; Curve Fitting

• Source: Sanz, H., J. J. Aponte, J. Harezlak, Y. Dong, A. Ayestaran, A. Nhabomba, M. Mpina, et al. 2017. “drLumi: An open-source package to manage data, calibrate, and conduct

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Metaviz: interactive statistical and visual analysis of metagenomic data

• Authors : Wagner, Justin; Chelaru, Florin; Kancherla, Jayaram

• Source: Wagner, Justin, Florin Chelaru, Jayaram Kancherla, Joseph N Paulson, Alexander Zhang, Victor Felix, Anup Mahurkar, Niklas Elmqvist, and Héctor Corrada Bravo. 2018. “Metaviz: interactive statistical

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