Within the MAARC, the Data and Analytics Support Core (DASC) plays a key role by providing fundamental data and analytic services to all CRCs. We shall accomplish this with the following aims:
Aim 1. Establish rigorous standards for the design, conduct and analysis of all trials and other data collection activities funded by JCOIN to ensure that the data collected: (1) are of the greatest scientific value; (2) are analyzed in appropriate ways using advanced statistical and other analytic methods, as necessary; (3) may be combined across different studies and with external data sources to increase power, permit replication, and answer new research questions; and (4) may be shared with other researchers while protecting participant confidentiality.
Aim 2. Create a secure, scalable computing infrastructure based on the proven, open-source Gen3 Data Commons platform to facilitate: (1) compiling and archiving harmonized data from the CRCs and other sources using common data elements (CDEs) from NIH's repository, whenever possible; (2) performing meta-analyses using data from multiple sites; (3) collaborative analyses using shared data, software and/or analytic methods; and (4) access to data within the JCOIN network and by the research community.
Aim 3. Provide integrated, comprehensive resources to individual JCOIN CRCs for data collection and management including: (1) identifying and designing instruments for data collection including cost and quality of life measures, using the PhenX toolkit whenever possible; (2) software tools for data collection, including access to REDCap (including mobile interface) and to the newly-developed Computerized Adaptive Test- Substance Abuse (CAT-SA); (3) software tools and workflows for data cleaning, QC and management; and (4) procedures for protecting participant confidentiality including an honest broker service.
Aim 4. Provide technical assistance to individual CRCs in a variety of analytic methods including: (1) advanced statistical methods for the design and analysis of randomized, controlled trials as well as meta- analyses of multiple studies; (2) methods for the coding and analysis of structured, qualitative data; and (3) advanced computational methods for predictive analytics and analysis of spatial and social network data.
Aim 5. In coordination with the Administrative Core, design and implement a wholistic approach to broad sharing of JCOIN resources: (1) create and maintain a public website for distribution of information about CRC studies and datasets available; (2) extend the Data Commons to include public-facing tools for exploring available datasets at an aggregate level; (3) develop and implement a governance model for the Data Commons which permits researchers to request and access data while maintaining appropriate safeguards to protect participant confidentiality; and (4) conduct training in using data and computational resources for members of the network and screencasts for public distribution.
