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Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time-and how this affects applications

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Forest Ecosystems 2024年第1期11卷 24-31页

作者： Goran Ståhl Terje Gobakken Svetlana Saarela Henrik J.Persson Magnus Ekstrom Sean P.Healey Zhiqiang Yang Johan Holmgren eva lindberg Kenneth Nystrom Emanuele Papucci Patrik Ulvdal Hans OleØrka Erik Næsset Zhengyang Hou Håkan Olsson Ronald E.McRoberts Department of Forest Resource Management Swedish University of Agricultural Sciences90183UmeåSweden Faculty of Environmental Sciences and Natural Resource Management Norwegian University of Life SciencesÅsNorway USDA Forest Service Rocky Mountain Research StationOgdenUTUSA The Key Laboratory for Silviculture and Conservation of Ministry of Education Beijing Forestry UniversityBeijing100083China Department of Forest Resources University of MinnesotaSt.PaulMNUSA

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for ***,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of *** such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of *** this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary *** this point of view,model-based predictors are typically ***,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely *** suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being *** show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to underestimating large true ***,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias *** argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

关键词： Bias Model-based inference Design-based inference

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Essentials of Teamcare in Randomized Controlled Trials of Multidisciplinary or Interdisciplinary Interventions in Somatic Care:A Systematic Review

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Open Journal of Nursing 2015年第12期5卷 1089-1101页

作者： Bengt Fridlund Ewa K.Andersson Sidona-Valentina Bala Gull-Britt Dahlman Anna K.Ekwall Stinne Glasdam Ami Hommel Catharina lindberg eva I.Persson Andreas Rantala Annica Sjostrom-Strand Jonas Wihlborg Karin Samuelson Department of Health Sciences Lund UniversityLundSweden School of Health&Welfare Jonkoping UniversityJonkopingSweden Department of Health Blekinge Institute of TechnologyKarlskronaSweden

Background: Teamcare should, like all patient care, also contribute to evidence-based practice (EBP). Randomized controlled trials (RCTs) focusing on teamcare have been performed but no study has addressed its essentials. How far this EBP has progressed in different health aspects is generally established in systematic reviews of RCTs. Aim: The aim is to determine the essentials of teamcare including the nurse profession in RCTs of multi- or interdisciplinary interventions in somatic care focusing on the stated context, goals, strategies, content as well as effectiveness of quality of care. Methods: A systematic review was performed according to Cochrane review assumptions to identify, appraise and synthesize all empirical evidence meeting pre-specified eligibility criteria. The PRISMA statement guided the data selection process of 27 articles from PubMed and CINAHL. Results: Eighty-five percent of RCTs in somatic care showed a positive effectiveness of teamcare interventions, of which interdisciplinary ones showed a greater effectiveness compared with the multidisciplinary approach (100% vs 76%). Also theory-based RCTs presented higher positive effectiveness (85%) compared with non-theory-based RCTs (79%). The RCTs with positive effectiveness showed greater levels for professional-centered ambition in terms of goals and for team-directed initiatives in terms of strategy, and a significantly higher level for patient-team interaction plans in terms of content was shown. Conclusions: Teamcare RCTs are still grounded in the multidisciplinary approach having a professional-centered ambition while interdisciplinary approaches especially those that are theory-based appear to be essential with regard to positive effectiveness and preferable when person-centered careis applied.

关键词： Teamcare Randomized Controlled Trial Somatic Care Systematic Review

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