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      Knee osteoarthritis has doubled in prevalence since the mid-20th century

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          Most cited references 26

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          Osteoarthritis cartilage histopathology: grading and staging.

          Current osteoarthritis (OA) histopathology assessment methods have difficulties in their utility for early disease, as well as their reproducibility and validity. Our objective was to devise a more useful method to assess OA histopathology that would have wide application for clinical and experimental OA assessment and would become recognized as the standard method. An OARSI Working Group deliberated on principles, standards and features for an OA cartilage pathology assessment system. Using current knowledge of the pathophysiology of OA morphologic features, a proposed system was presented at OARSI 2000. Subsequently, this was widely circulated for comments amongst experts in OA pathology. An OA cartilage pathology assessment system based on six grades, which reflect depth of the lesion and four stages reflecting extent of OA over the joint surface was developed. The OARSI cartilage OA histopathology grading system appears consistent and simple to apply. Further studies are required to confirm the system's utility.
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            Is Open Access

            Matching Methods for Causal Inference: A Review and a Look Forward

              (2010)
            When estimating causal effects using observational data, it is desirable to replicate a randomized experiment as closely as possible by obtaining treated and control groups with similar covariate distributions. This goal can often be achieved by choosing well-matched samples of the original treated and control groups, thereby reducing bias due to the covariates. Since the 1970s, work on matching methods has examined how to best choose treated and control subjects for comparison. Matching methods are gaining popularity in fields such as economics, epidemiology, medicine and political science. However, until now the literature and related advice has been scattered across disciplines. Researchers who are interested in using matching methods---or developing methods related to matching---do not have a single place to turn to learn about past and current research. This paper provides a structure for thinking about matching methods and guidance on their use, coalescing the existing research (both old and new) and providing a summary of where the literature on matching methods is now and where it should be headed.
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              MatchIt: Nonparametric Preprocessing for Parametric Causal Inference

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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                August 29 2017
                August 29 2017
                : 114
                : 35
                : 9332-9336
                Article
                10.1073/pnas.1703856114
                © 2017

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