Zobrazeno 1 - 10 of 46 pro vyhledávání: '"Mariel M. Finucane"'
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Akademický článek
Regional functional connectivity predicts distinct cognitive impairments in Alzheimer’s disease spectrum
Autor: Kamalini G. Ranasinghe, Leighton B. Hinkley, Alexander J. Beagle, Danielle Mizuiri, Anne F. Dowling, Susanne M. Honma, Mariel M. Finucane, Carole Scherling, Bruce L. Miller, Srikantan S. Nagarajan, Keith A. Vossel
Publikováno v: NeuroImage: Clinical, Vol 5, Iss C, Pp 385-395 (2014)
Understanding neural network dysfunction in neurodegenerative disease is imperative to effectively develop network-modulating therapies. In Alzheimer’s disease (AD), cognitive decline associates with deficits in resting-state functional connectivit
Externí odkaz: https://doaj.org/article/45cf301f65c440b18070cb611f2f085d
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4
Risk of Workforce Exit due to Disability: State Differences in 2003–2016
Autor: Mariel M. Finucane, Ignacio Martinez, Yonatan Ben-Shalom
Publikováno v: Journal of Survey Statistics and Methodology. 9:209-230
A better understanding of trends in workforce exit due to disability and how these trends vary across states and subgroups can help federal and state policymakers identify both individual-level and state-level factors associated with increased risk o
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cd591dcf35cf298d962d1b3ff977e671
https://doi.org/10.1093/jssam/smab005
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6
Speaking on Data’s Behalf: What Researchers Say and How Audiences Choose
Autor: Jesse Chandler, Ignacio Martinez, Mariel M. Finucane, Jeffrey G. Terziev, Alexandra Resch
Publikováno v: Evaluation Review. 44:325-353
Background: Bayesian statistics have become popular in the social sciences, in part because they are thought to present more useful information than traditional frequentist statistics. Unfortunately, little is known about whether or how interpretatio
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::daf992a1a045bce41a6b5953ff304684
https://doi.org/10.1177/0193841x19834968
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7
Revolutionizing Estimation and Inference for Program Evaluation Using Bayesian Methods
Autor: Lauren Vollmer, Mariel M. Finucane, Randall Brown
Publikováno v: Evaluation Review. 44:295-324
Background: Policy makers seek to replace the “thumbs up–thumbs down” of conventional hypothesis testing with statements about the probability that program effects on key outcomes exceed policy-relevant thresholds. Objective: We develop a Bayes
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5d2e362fefd652d6863334bb856d863
https://doi.org/10.1177/0193841x18815817
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8
Akademický článek
Children's height and weight in rural and urban populations in low-income and middle-income countries: a systematic analysis of population-representative data
Autor: Christopher J Paciorek, PhD, Gretchen A Stevens, DSc, Mariel M Finucane, PhD, Prof. Majid Ezzati, PhD
Publikováno v: The Lancet Global Health, Vol 1, Iss 5, Pp e300-e309 (2013)
Background: Urban living affects children's nutrition and growth, which are determinants of their survival, cognitive development, and lifelong health. Little is known about urban–rural differences in children's height and weight, and how these dif
Externí odkaz: https://doaj.org/article/421b6e51bec84e6a96fdcf83afe76500
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9
THE INTERNAL AND EXTERNAL VALIDITY OF THE REGRESSION DISCONTINUITY DESIGN: A META‐ANALYSIS OF 15 WITHIN‐STUDY COMPARISONS
Autor: Jared Coopersmith, Lauren Vollmer, Rebecca Morris, Jelena Zurovac, Mariel M. Finucane, Thomas D. Cook, Duncan Chaplin
Publikováno v: Journal of Policy Analysis and Management. 37:403-429
Theory predicts that regression discontinuity (RD) provides valid causal inference at the cutoff score that determines treatment assignment. One purpose of this paper is to test RD's internal validity across 15 studies. Each of them assesses the corr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d53a2fc0dcc6472326512879d7172f74
https://doi.org/10.1002/pam.22051
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10
What Works for Whom? A Bayesian Approach to Channeling Big Data Streams for Public Program Evaluation
Autor: Scott Cody, Mariel M. Finucane, Ignacio Martinez
Publikováno v: American Journal of Evaluation. 39:109-122
In the coming years, public programs will capture even more and richer data than they do now, including data from web-based tools used by participants in employment services, from tablet-based educational curricula, and from electronic health records
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d02774345601d19ca7f918e2381321e1
https://doi.org/10.1177/1098214017737173
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