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      Integration of different geospatial factors to delineate groundwater potential zones using multi-influencing factors under remote sensing and GIS environment: a study on Dakshin Dinajpur district, West Bengal, India

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          The kappa statistic in reliability studies: use, interpretation, and sample size requirements.

          This article examines and illustrates the use and interpretation of the kappa statistic in musculoskeletal research. The reliability of clinicians' ratings is an important consideration in areas such as diagnosis and the interpretation of examination findings. Often, these ratings lie on a nominal or an ordinal scale. For such data, the kappa coefficient is an appropriate measure of reliability. Kappa is defined, in both weighted and unweighted forms, and its use is illustrated with examples from musculoskeletal research. Factors that can influence the magnitude of kappa (prevalence, bias, and non-independent ratings) are discussed, and ways of evaluating the magnitude of an obtained kappa are considered. The issue of statistical testing of kappa is considered, including the use of confidence intervals, and appropriate sample sizes for reliability studies using kappa are tabulated. The article concludes with recommendations for the use and interpretation of kappa.
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            Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques

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              Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: A case study at Mehran Region, Iran

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Sustainable Water Resources Management
                Sustain. Water Resour. Manag.
                Springer Science and Business Media LLC
                2363-5037
                2363-5045
                February 2022
                January 30 2022
                February 2022
                : 8
                : 1
                Article
                10.1007/s40899-022-00630-3
                d39953f0-9d27-4d7b-81ff-7289f17f779e
                © 2022

                https://www.springer.com/tdm

                https://www.springer.com/tdm

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