A Wilson, Core C (Data Management and Statistics) Summary The objectives of Core C are to (a) facilitate acquisition of shared data and project specific data for Projects 1- 5, (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 Investigator, the Executive Committee, and the Scientific Advisory Committee in providing scientific oversight and administration of the Texas Center for Learning Disabilities (TCLD), (d) facilitate communication and sharing of data among investigators through state of the art computer networking and HIPAA Compliant shared, distributed workspaces, and data movement (e) provide statistical analysis and/or support to Projects 1-5, and (f) to collaborate with investigators in the conceptualization and execution of cross-project, integrative analyses from the current projects, including synergistic activities that might incorporate data collected in the prior TCLD awards. These objectives are organized into three specific aims targeting: (1) Data Acquisition; (2) Data Management; and (3) Data Analysis. Through these aims Core C seeks to enhance the scientific rigor and reproducibility of research throughout the center by providing investigators access to sustainable, cost effective, cutting-edge intellectual and technical resources, prioritizing quality control, scientific integrity, and productivity, and promoting advanced statistical approaches to individual study aims and interdisciplinary, cross-project synergies. Dr. David Francis, an experienced methodologist, is the Core Director. He will supervise all activities of Core C, working closely with other experienced methodologists (Taylor, Roberts, Cirino) to establish databases, supervise quality control, and perform statistical analyses. The resources of the Texas Institute for Measurement, Evaluation, and Statistics (TIMES) are extensive and will be available to the Center. The Core has the capacity for efficient, high quality data acquisition, sophisticated data management, and complex statistical analysis, with an established track record in all three areas. The project publications that involve data listed in the current progress reports reflect usage of Core C for data management and analysis over the past 5 years.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Specialized Center (P50)
Project #
5P50HD052117-13
Application #
9843481
Study Section
Special Emphasis Panel (ZHD1)
Project Start
Project End
Budget Start
2020-01-01
Budget End
2020-12-31
Support Year
13
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Houston
Department
Type
DUNS #
036837920
City
Houston
State
TX
Country
United States
Zip Code
77204
Wanzek, Jeanne; Stevens, Elizabeth A; Williams, Kelly J et al. (2018) Current Evidence on the Effects of Intensive Early Reading Interventions. J Learn Disabil 51:612-624
Roe, Mary Abbe; Martinez, Joel E; Mumford, Jeanette A et al. (2018) Control Engagement During Sentence and Inhibition fMRI Tasks in Children With Reading Difficulties. Cereb Cortex 28:3697-3710
Quinn, Jamie M (2018) Differential Identification of Females and Males with Reading Difficulties: A Meta-Analysis. Read Writ 31:1039-1061
Vaughn, Sharon; Roberts, Garrett J; Miciak, Jeremy et al. (2018) Efficacy of a Word- and Text-Based Intervention for Students With Significant Reading Difficulties. J Learn Disabil :22219418775113
Hernandez, Arturo E; Claussenius-Kalman, Hannah L; Ronderos, Juliana et al. (2018) Symbiosis, Parasitism and Bilingual Cognitive Control: A Neuroemergentist Perspective. Front Psychol 9:2171
Cirino, Paul T; Ahmed, Yusra; Miciak, Jeremy et al. (2018) A framework for executive function in the late elementary years. Neuropsychology 32:176-189
Williams, Victoria J; Juranek, Jenifer; Cirino, Paul et al. (2018) Cortical Thickness and Local Gyrification in Children with Developmental Dyslexia. Cereb Cortex 28:963-973
Cho, Eunsoo; Capin, Philip; Roberts, Greg et al. (2018) Examining Predictive Validity of Oral Reading Fluency Slope in Upper Elementary Grades Using Quantile Regression. J Learn Disabil 51:565-577
Quinn, Jamie M; Wagner, Richard K (2018) Using Meta-analytic Structural Equation Modeling to Study Developmental Change in Relations Between Language and Literacy. Child Dev 89:1956-1969
Nikki Arrington, C; Kulesz, Paulina A; Juranek, Jenifer et al. (2017) White matter microstructure integrity in relation to reading proficiency?. Brain Lang 174:103-111

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