The Infant Health and Development Program (IHDP) is a randomized controlled study designed to evaluate the effect of home visit from specialist doctors on the cognitive test scores of premature infants. The datasets is first used for benchmarking treatment effect estimation algorithms in Hill [35], where selection bias is induced by removing non-random subsets of the treated individuals to create an observational dataset, and the outcomes are generated using the original covariates and treatments. It contains 747 subjects and 25 variables.
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This dataset represents a group of paper records (a "series") within the Marie C. McCormick papers, 1956-2016 (inclusive), 1968-2009 (bulk), which can be accessed on-site at the Center for the History of Medicine at the Francis A. Countway Library of Medicine in Boston, Massachusetts. The series consists of administrative and regulatory records generated and compiled by Marie C. McCormick as a product of her service as Principal Investigator of phase IV of the Infant Health and Development Program. The Infant Health and Development Program (IHDP) consisted of four phases, and was concerned with the short- and long-term outcomes of low birthweight and high-risk pregnancies. For records from the first three phases, please see the “Infant Health and Development Program, Phases I-III Records, 1984-2002” dataset. Regulatory records include: survey instruments; protocols and methodologies; and codebooks. Administrative records include: institutional review board certification records and safety plan activation records for each site; grant applications; budgets; reports; subject lists; meeting agendas; and administrative correspondence. Frequent topics include: engagement and motivation in school; behavior and mental health; cognitive and linguistic ability; health status; mothers’ supervisory attitudes and strategies; mothers’ aspirations for their children; mothers’ coping and mental health; differences between lighter and heavier low-birthweight children; and differences between more and less affluent families. Series also includes: occasional summarized, analyzed, and assessment data tables and charts; manuscript drafts and collected publications; and five CDs and one DVD, containing SAS and SPSS dataset files and administrative, regulatory, and publishing records. More IHDP records may be found in the “Infant Health and Development Program, Phases I-III Records, 1984-2002” and “Infant Health and Development Program, Phase IV Electronic Records, 2000-2016” datasets. Data and associated records are accessible onsite at the Center for the History of Medicine per the conditions governing access described below. Conditions Governing Access to Original Collection Materials: The series represented by this dataset includes longitudinal patient information that is restricted for 80 years from the most recently dated records in the series, personnel information that is restricted for 80 years from the date of record creation, and Harvard University records that are restricted for 50 years from the date of record creation. Access to electronic records is also premised on the availability of a computer station, requisite software, and/or the ability of Public Services staff to review and/or print out records of interest in advance of an on-site visit. Researchers should contact Public Services for more information. The Marie C. McCormick papers were processed with grant funding from the Andrew W. Mellon Foundation, as awarded and administered by the Council on Library and Information Resources (CLIR) in 2016. View the Marie C. McCormick Papers finding aid for a full collection inventory of both paper and digital records, and for more information about accessing and using the collection.
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The Infant Health and Development Program (IHDP) is a randomized controlled study designed to evaluate the effect of home visit from specialist doctors on the cognitive test scores of premature infants. The datasets is first used for benchmarking treatment effect estimation algorithms in Hill [35], where selection bias is induced by removing non-random subsets of the treated individuals to create an observational dataset, and the outcomes are generated using the original covariates and treatments. It contains 747 subjects and 25 variables.