7 research outputs found

    The adjusted<sup>*</sup> association between the self-reported outcome variables and non-odor related explanatory variables in communities near AFOs.

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    <p>*</p><p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009530#pone.0009530-Hoopmann1" target="_blank">[42]</a> Adjusted for gender, oldest sibling, experienced street noise (clearly vs. very little), actual smoking (yes vs. no), education level, breastfed at least 4 months (yes vs. no), mold (yes vs. no), contact with cats at a young age (yes vs. no), rug/Carpeted floor (yes vs. no), parental atopy.</p><p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009530#pone.0009530-Mirabelli2" target="_blank">[68]</a> Adjusted for individual-level characteristics (gender, age, race, Hispanic ethnicity, economic status, smoking status, exposure to second-hand smoke at home, and use of a gas stove more than once per month) and school-level characteristics (rural locale, indoor air quality, and reports of other non-livestock industries nearby).</p><p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009530#pone.0009530-Radon3" target="_blank">[62]</a> Adjusted for age (5 categories), sex, active and passive smoke exposure, level of education, number of siblings, parental allergies.</p><p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009530#pone.0009530-Avery1" target="_blank">[69]</a> Adjusted for fixed effects for odor, time of day, and day, and random effects for cluster, person within cluster, odor, and time of day.</p><p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009530#pone.0009530-Schiffman3" target="_blank">[65]</a> Two-way analysis of variance.</p

    Thirty sampled decision support technologies: sample characteristics and adjusted full IPDASi (v3) <sup>*</sup> and SF scores based on duplicate assessment, with 95% confidence limits.

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    *<p>Adjusted scores: scores from the two raters were adjusted to take account of their personal propensity to give higher or lower scores. Components of variation were modelled by Bayesian modelling (Markov chain Monte Carlo) using WinBugs software, leading to estimated confidence intervals.</p><p><b>Abbreviations</b>: (APCC: Australian Prostate Cancer Collaboration; Barratt, UoS: University of Sydney; Crouch, Baylor: Baylor College of Medicine; Col, CORE: Center for Outcomes Research and Evaluation; Elwyn, CU: Cardiff University; FIMDM: Foundation for Informed Medical Decision Making; Lawrence, STVHCS: South Texas Veterans Health Care System; Leighl, UoT: University of Toronto; MCC: Michigan Cancer Consortium Prostate Cancer Action Committee; MIDIRS: Midwife Information and Resource Service; NERI: New England Research Institutes; OHDeC: Ottawa Health Decision Centre; Shorten, ACM: Australian College of Midwives; Taylor, GU: Georgetown University; US CDC: Centers for Disease Control and Prevention; Wakefield MU, Macquarie University).</p
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