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Journal of Research in Medical Sciences، جلد ۱۹، شماره ۱، صفحات ۰-۰
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عنوان انگلیسی Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies
چکیده انگلیسی مقاله Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinalscale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables.
کلیدواژه‌های انگلیسی مقاله
نویسندگان مقاله حمید رضا marateb | hamid reza marateb


مرجان منصوریان | marjan mansourian


پیمان ادیبی | peyman adibi


dario farina | dario farina


نشانی اینترنتی http://jrms.mui.ac.ir/index.php/jrms/article/view/9827
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زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده Review Articles
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