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YABACI TAK, AYŞEGÜL

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Author: Ercan, İlker × Has files: true ×

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    PublicationOpen Access
    Statistical Errors in Medical Residency Theses
    (2022-04-01T00:00:00Z) Yabacı Tak, Ayşegül; Can, Fatma Ezgi; Kaşkır Kesin, Fisun; Ahmadian Tetik, Robab; Ercan, İlker; YABACI TAK, AYŞEGÜL
    Objective: The aim of this study is to evaluate the theses of residency in medicine in terms of statistical errors made and thus to contribute to the production of quality scientific publications by ensuring that scientific publishers in the Add of medicine are sensitive and careful about statistics when doing their work. Methods: In this study, we investigated 321 thesis theses which are defended from 6 different universities arc obtained from the database of the Turkish Higher Education Council. The investigation is was conducted in terms of "Errors Related to p-values", "Errors Related to Tests", "Mathematical Notation Errors", "Statistical Symbol Errors", "Inappropriate Interpretation", "Presentation of The the Statistical Method Analysis and Results in The the Incorrect Section of The the Manuscript", "Errors in Summarizing Data","Incomprehensible Statistical Terms" and "Errors in Statistical Terminology" Results: There was at least one statistical error in all 321 medicine residency theses examined. The most common error was "errors in summarizing data" with a ratio of 70.1% (n=225), while the least common error was "incomprehensible statistical expressions" with a ratio of 14.3% (n=46). Conclusion: As a result, both researchers and consultants who undertake scientific studies have a responsibility to minimize these errors. To prevent statistical errors, students who are doing residency in medicine arc required to receive the necessary training in statistical literacy, to have basic statistical knowledge, and to receive consultancy from a biostatistics expert for statistical evaluations. Students who residency in medicine in preventing statistical errors are required to receive the necessary training in statistical literacy, to have basic statistical knowledge, and to receive consultancy from a biostatistics expert for statistical evaluations.
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    PublicationOpen Access
    Statistical shape analysis of hand and wrist in paediatric population on radiographs
    (2020-05-01T00:00:00Z) Koç, Ural; Ercan, İlker; Özdemir, Senem; Bolu, Semih; Yabacı, Ayşegül; Taydaş, Onur; YABACI TAK, AYŞEGÜL
    Background/aim: The goal of this study was to compare differences in hand and wrist shapes and to evaluate these according to growth and allometry in children on radiographs related to bone age. Materials and methods: The study included 263 males and 189 females. A total of 452 left hand and wrist radiographs were retrospectively collected. Standard anatomical landmarks marked on radiographs. Results: There were seen to be significant differences in comparisons of hand and wrist shapes according to sex (P = 0.009). The most suitable model in the growth models was seen as the Gompertz growth model for both females and males (model P < 0.001). For the relationship between shape and size to evaluate allometry, significant models were obtained in females (model P = 0.017, MSE = 0.0002) and in males (model P < 0.001, MSE = 0.0002). In our study, the difference between the sexes was found mostly in the radiocarpal region. It was observed that the deformation of the carpal bones started in the distal row carpal bones. Conclusion: Significant differences were found in hand and wrist shapes according to sex. Models for growth and allometry of hand and wrist shapes were found to be significant in children.