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Data sources are both administrative data and surveys.
Using both administrative data and four separate longitudinal studies sponsored by the U.S. Department of Education's National Center for Education Statistics (NCES), we evaluate several prominent explanations for the persisting gender gap in STEM fields related to mathematics performance and background and general life goals, and find that none of them are empirically satisfactory.
We made use of both administrative data and data from portal tracking systems to address our secondary hypotheses, to cross-validate survey responses from PCPs and patients with actual portal use before and during the intervention period.
Location of care was coded from three variables assessing setting and sector obtained from both administrative data and survey data; codes were applied only to cases where these two sources were concordant.
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This includes both administrative data on child outcomes and use of public services and child centred assessments of national surveys.
A recent study by Woo et al [ 16] considered both hospital administrative data and a clinical database that captured height and weight for all children admitted to hospital.
Furthermore, since treatment would have been included in both the administrative data and the extended models, their exclusion should not have changed our results.
A third limitation to this research that is inherent in both health administrative data and EMRs is a bias towards individuals who use health services; therefore, our dataset would only include those individuals receiving medical care.
To assess the agreement between self-reported co-morbidity and administrative databases, we calculated the proportion of subjects with each co-morbid condition based on: self-report only, administrative data sources only, both self-report and administrative data, and either self-report or administrative data.
This result holds both for achievement measured using administrative data, and for outcomes (such as performance on standardized exams) that the researchers themselves measured.
But our method for linking these costs to a worker's employment status requires both national-level program enrollments and administrative data, and individual-level survey data on the benefits consumption of workers.
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