Using Person Fit Statistics to Detect Outliers in Survey Research
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چکیده
منابع مشابه
Using Person Fit Statistics to Detect Outliers in Survey Research
Context: When working with health-related questionnaires, outlier detection is important. However, traditional methods of outlier detection (e.g., boxplots) can miss participants with "atypical" responses to the questions that otherwise have similar total (subscale) scores. In addition to detecting outliers, it can be of clinical importance to determine the reason for the outlier status or "aty...
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Two frequently used parametric statistics of person-fit with the dichotomous Rasch model (RM) are adjusted and compared to each other and to their original counterparts in terms of power to detect aberrant response patterns in short tests (10, 20, and 30 items). Specifically, the cube root transformation of the mean square for the unweighted person-fit statistic, t, and the standardized likelih...
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The Law School Admission Council (LSAC) is a nonprofit corporation that provides unique, state-of-the-art products and services to ease the admission process for law schools and their applicants worldwide. Currently, 222 law schools in the United States, Canada, and Australia are members of the Council and benefit from LSAC's services. All law schools approved by the American Bar Association ar...
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Outlier detection is an important task in data mining because outliers can be either useful knowledge or noise. Many statistical methods have been applied to detect outliers, but they usually assume a given distribution of data and it is difficult to deal with high dimensional data. The Statistical Learning Theory (SLT) established by Vapnik et aI. provides a new way to overcome these drawbacks...
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ژورنال
عنوان ژورنال: Frontiers in Psychology
سال: 2017
ISSN: 1664-1078
DOI: 10.3389/fpsyg.2017.00863