AComparison of Methods for Estimating State Subgroup Performance on the National Assessment of Educational Progress:

Thesis advisor: Henry BraunThe State NAEP program only reports the mean achievement estimate of a subgroup within a given state if it samples at least 62 students who identify with the subgroup. Since some subgroups of students constitute small proportions of certain states’ general student populations, these low-incidence groups of students are seldom sufficiently sampled to meet this rule-of-62 requirement. As a result, education researchers and policymakers are frequently left without a full understanding of how states are supporting the learning and achievement of different subgroups of students.Using grade 8 mathematics results in 2015, this dissertation addresses the problem by comparing the performance of three different techniques in predicting mean subgroup achievement on NAEP. The methodology involves simulating scenarios in which subgroup samples greater or equal to 62 are treated as not available for calculating mean achievement estimates. These techniques comprise an adaptation of Multivariate Imputation by Chained Equations (MICE), a common form of Small Area Estimation known as the Fay-Herriot model (FH), and a Cross-Survey analysis approach that emphasizes flexibility in model specification, referred to as Flexible Cross-Survey Analysis (FLEX CS) in this study. Data used for the prediction study include public-use state-level estimates of mean subgroup achievement on NAEP, restricted-use student-level achievement data on NAEP, public-use state-level administrative data from Education Week, the Common Core of Data, the U.S. Census Bureau, and public-use district-level achievement data in NAEP-referenced units from the Stanford Education Data Archive. To evaluate the accuracy of the techniques, a weighted measure of Mean Absolute Error and a coverage indicator quantify differences between predicted and target values. To evaluate whether a technique could be recommended for use in practice, accuracy measures for each technique are compared to benchmark values established as markers of successful prediction based on results from a simulation analysis with example NAEP data. Results indicate that both the FH and FLEX CS techniques may be suitable for use in practice and that the FH technique is particularly appealing. However, before definitive recommendations are made, the analyses from this dissertation should be conducted employing math achievement data from other years, as well as data from NAEP Reading.Thesis (PhD) — Boston College, 2021.Submitted to: Boston College. Lynch School of Education.Discipline: Educational Research, Measurement and Evaluation

Matthew Chingos & The Urban Institute

Materials related to "Breaking the Curve: Promises and Pitfalls of Using NAEP Data to Assess the State Role in Student Achievement" (Chingos, 2015).<br><br

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Variables:<br>*R4 = NAEP scores<br>**BA = percent of children in homes whose head of household has a BA or higher<br>**POV = percent of children in homes at 100% or higher of the federal poverty line (household of 4).<br>**CANH: percent of children identified as Caucasian non-Hispanic or Asian non-Hispanic. <br> <br>*Source = National Center for Education Statistics<br>**Source = KidsCount via American Community Survey section of the US CENSUS <br><br

Supplementary Material for: Commentary on ‘Early (< 7 days) systemic postnatal corticosteroids for prevention of bronchopulmonary dysplasia in preterm infants’

Medicin

Child Care Coverage and Parents’ Work Schedule Alignment: How Do Parents Address Gaps?

In this secondary analysis of the 2012 and 2019 National Survey of Early Care and Education (NSECE) data, we plan to conduct rigorous research that will address key questions of interest to federal and state Child Care and Development Fund (CCDF) leaders and child care decision makers. We will conduct analyses to address questions about variations in parents’ access to child care that meets the needs of their work schedules, the choices parents make about how to address gaps between child care coverage and work schedules, and the factors that influence the presence of coverage gaps and the ways parents choose to address them

EBNEO commentaries: An ongoing collaboration advancing evidence-based neonatal care

Editorial. First published: 21 January 2021In February 2017, Acta Paediatrica announced a collaboration1 with the International Society for Evidence‐Based Neonatology (EBNEO) to produce and publish EBNEO commentaries. We are pleased to report the collaboration continues with 85 commentaries from EBNEO reviews published at the close of 2020. EBNEO is a ‘A non‐profit organisation that nourishes a vision that all neonatal care should be firmly built on best available evidence. The vision includes as short a passage from research‐based knowledge to implementation in neonatal care (translation), thereby improving survival, decreasing morbidities and promoting long‐lasting health for newborn infants’. EBNEO reviews are an important part of this goal. The reviews are peer‐reviewed appraisals of studies relevant to neonatal care. The review consists of a structured abstract that highlights important study details, including methods, statistical analyses and key results of the critiqued study. It concludes with a 500‐word commentary reflecting on the findings in the context of evidence‐based neonatal practice. This commentary is published by Acta Paediatrica and is linked to the EBNEO website (https://ebneo.org/) where the full review can be accessed. EBNEO commentaries are indexed on PubMed and are freely available from the Acta Paediatrica home page. EBNEO reviews are a key part of our organisational mission to increase exposure, dissemination and accessibility of research findings relevant to evidence‐based neonatal practice. However, our work is not limited to this initiative. In early 2017, we introduced #ebneoalerts, an effort to constantly screen, curate and disseminate neonatal evidence‐based literature. We recognised that as the yearly global output of publications relevant to neonatology grows, providers are increasingly unable to remain ‘up‐to‐date’ through individual efforts. In turn, our dissemination approach was influenced by the growing influence of social media in academic medicine and society more broadly. We organised an international group of neonatologists with interest and training in neonatal research and developed an approach to collaboratively curate newly published articles and generate brief summaries of key findings through digital graphics and posts disseminated through social media and a monthly email newsletter. Each post includes a hyperlink to the article on the journal website to encourage further reading. As of December 2020, these dissemination efforts have reached over 20,000 ‘followers’ or subscribers across the globe. Further, since 2011, we have held biennial conferences in partnership with international institutions and organisations, highlighting both clinical and methodological topics of relevance to evidence‐based neonatal practice.Amy Keir, Nicolas Bamat, Elaine Boyle, Omar ElKhateeb, Clyde Wrigh