Chris Schatschneider, Ph.D. - US grants

Core B plays the role of the traditional Data Coordinating Center in a multi-site research project. As such, Core B has been designed to provide support to Projects I-IV in three broadly defined areas-Data Acquisition, Data Management and Communications, and Data Analysis. The specific objectives of Core B are to (a) facilitate acquisition of project specific data for Projects I-V5, (b) develop tools and procedures for ensuring and monitoring the accuracy and confidentiality of all collected data, (c) develop tools and procedures to aid the Principal Investigators, the Executive Committee, and the Scientific Advisory Committee in providing scientific oversight and administration of the Program Project, (d) facilitate communication and sharing of data among investigators through state of the art computer networking, and (e) provide statistical support and analyses to investigators in the evaluation of the Project hypotheses.

Project III entails an examination of the Florida's Progress Monitoring and Reporting Network (PMRN)[unreadable] database containing multiple measures of multiple reading constructs on 300,000 children attending[unreadable] underachieving schools in the state of Florida. Approximately 124,000 new children enter the database each[unreadable] year in one of the six grade levels in which data are collected: kindergarten through Fifth grade. This[unreadable] extensive database is uniquely equipped to answer questions related to each of the six Center grant goals. It[unreadable] will be used to estimate the percentages of struggling readers who fit alternative classification criteria for[unreadable] learning disability in various domains (e.g., impaired decoding, impaired comprehension, etc.). It also will be[unreadable] used to examine how alternative classification criteria for learning disability (e.g., unexplained low[unreadable] achievement, inadequate growth) are related (i.e., do they classify the same children as learning disabled).[unreadable] We will examine the predictive validity of alternative classification criteria for learning disability, amd[unreadable] environmental variables in relation to alternative classifications (e.g., SES, performance level of the school,[unreadable] etc.) and their predictive validity. For the quantitative genetic studies, we will identify an usually large[unreadable] number (N = 9,000) of identical and fraternal twins within the PMRN sample in order to examine genetic and[unreadable] environmental influence on reading constructs, their relationships to each other, and to their growth over[unreadable] time. We will use the sample within the PMRN to examine differential heritability of reading ability vs.[unreadable] disability defined in alternative ways.

The overall Program Project proposes to use a considerable number of advanced statistical techniques to address complex problems. Core C plays the role of providing data analysis assistance to the Projects in order to support their efforts to evaluate the project aims and hypotheses. The specific objectives of Core C are to provide data analytical support and analyses to investigators in the evaluation of the project hypotheses and to facilitate communication and sharing of data among investigators Investigators from all the projects will be able to access the services of the Core, which range from consultation on research design issues that may arise during the course ofthe projects, data analysis consultation to the actual statistical modeling of collected project data.

The overall Program Project proposes to use a considerable number of advanced statistical techniques to address complex problems. Core C plays the role of providing data analysis assistance to the Projects in order to support their efforts to evaluate the project aims and hypotheses. The specific objectives of Core C are to provide data analytical support and analyses to investigators in the evaluation of the project hypotheses and to facilitate communication and sharing of data among investigators Investigators from all the projects will be able to access the services of the Core, which range from consultation on research design issues that may arise during the course ofthe projects, data analysis consultation to the actual statistical modeling of collected project data.

ABSTRACT Analytics Core The Analytics Core (Core C) plays the role of providing statistical analysis assistance to the Projects in order to support their efforts to evaluate the project aims and hypotheses. The specific objectives of Core C are to provide data analytical support and analyses to investigators in the evaluation of the project hypotheses and to facilitate communication and sharing of data among investigators. Core C will also provide consultation to the individual projects in regards to best practices in data management.

PROJECT SUMMARY There is considerable interest in data sharing, encouraged by funding agencies which are requiring more detailed data-sharing plans, as well as greater attention and support from the scientific community towards rigorous, open, and reproducible science. With this project, we will build a domain-specific data repository, ?LDbase?, containing behavioral data from the field studying learning disabilities that will serve as a powerful resource for our community. We are uniquely qualified to build this repository. Our investigator team combines expertise in learning disabilities, advanced methodology, and research librarian techniques. LDbase will accelerate intellectual discovery by facilitating data reuse and reproducibility, ultimately building an enduring record that represents the richness, diversity, and complexity of the science done by learning disabilities researchers. We will achieve this through three specific aims: (1) Create a data repository representing a vast knowledge database on learning disabilities; (2) Release a powerful open access combined dataset and provide statistical training for combining datasets using integrative data analysis; and (3) Use integrated data to determine the most valid way to classify a reading disability for each child. LDbase will be seeded by data from six large research sites that will contribute large amounts of behavioral data from tens of thousands of participants, and then open to external data depositors and data users. With these high quality ?big data?, we will answer a fundamental question in the field concerning personalized classification of reading disability, showing the powerful applied usefulness of these data. LDbase will advance the sharing of learning disabilities related behavioral data as a powerful new tool to answer research questions not answerable without it, build a community of researchers invested in data sharing and open science practices, and establish a sustainable infrastructure to support the longevity of the project.