Statistical Core

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C. Data Management and Analysis Core 1. Objective The objective of the Data Management and Analysis Core is to continue to provide data management services and statistical expertise to Program Project investigators in a wide range of data acquisition and analysis activities. Integral to the goals of each project is the management and analysis of Core observational, interview, questionnaire, and behavioral data, as well as management and analysis of data from the individual projects. Data management activities draw on the considerable resources of the Data Management and Analysis Center (DMAC) at the Frank Porter Graham Child Development Center (FPG) at UNC and The Methodology Center (TMC) at PSD. Specific Aims of the Data Management and Analysis Core are to: 1) Implement the planned missing design in conjunction with the Executive Committee. 2) Develop and maintain data management strategies that process data collected in the common protocol and the individual projects efficiently and accurately. 3) Design and maintain integrated databases of project and common protocol data. 4) Develop and implement data analysis plans using innovative analytic methods for longitudinal data including variable-centered and person-centered approaches to address research questions in collaboration with project investigators. 5) To set in place a data archiving system for data sharing. These goals require the collaboration of experienced statisticians and computer programmers. The DMAC programmers have expertise in all aspects of quantitative data management, from the entry and tracking of data to the generation of analysis files and statistical programming. The DMAC and TMC statisticians collaborated with these and other investigators regarding design and statistical issues across many early childhood research projects. The Data Management and Analysis Core provides high level expertise to the Program Project in each of these areas. The use of an experienced data acquisition and analysis center to process and analyze data across the projects will provide both high levels of quality control and cost effectiveness. A central data acquisition and analysis center is especially important for this Program Project because data from each project contributes to the common protocol for use by all projects in addressing their hypotheses. In particular, executive functioning and self regulation measures collected by Project I, classroom observations and child cognitive/academic outcomes collected by Project II, and family process measures collected by Project III, and community measures from the core are primary predictor or outcome measures used in analyses by all projects. Central coordination of data processing and analysis will ensure the consistent and timely processing of these ¿data^for-all- inyestigatgrsv Careful documentation of data scoring, including the "reliability and distributions of summary variables, will facilitate the use of one project's data by other project investigators. The services provided by the Data Management and Analysis Core pertain to almost all phases of the research including design, data collection, data entry, and analysis. The main advantage of having a centralized facility for data management and computing is the ability to provide coordinated services that address the wide range of issues involved in these activities. By coordinating data processing activities for all projects, duplication of effort is reduced, efficiencies of data management and analyses are generated, and opportunities for higher level analysis across data sets from different projects are made available. Thus, maximum communication is obtained across all projects to further the understanding of data to be analyzed, as well as the statistical procedures for those analyses. Furthermore, synergy among projects is enhanced through having the same programmers and statisticians working across projects.