English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 18034/20233 (89%)
造訪人次 : 23355210      線上人數 : 501
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://ir.cnu.edu.tw/handle/310902800/31655


    標題: Development of a Microsoft Excel tool for applying a factor retention criterion of a dimension coefficient to a survey on patient safety culture
    作者: Chien, Tsair-Wei
    Shao, Yang
    Jen, Dong-Hui
    貢獻者: Chi Mei Med Ctr, Dept Med Res
    Chia Nan Univ Pharm & Sci, Dept Hosp & Hlth Care Adm
    Tongji Zhejiang Coll, Dept Elect & Informat Engn, Jiaxing
    Chi Mei Med Ctr, Dept Chinese Med
    關鍵字: Dimension coefficient
    Patient safety culture survey
    Visual basic for applications
    Area under receiver operating characteristic curve
    Parallel analysis
    日期: 2017-10-27
    上傳時間: 2018-11-30 15:51:44 (UTC+8)
    出版者: Biomed Central Ltd
    摘要: Background: Many quality-of-life studies have been conducted in healthcare settings, but few have used Microsoft Excel to incorporate Cronbach's a with dimension coefficient (DC) for describing a scale's characteristics. To present a computer module that can report a scale's validity, we manipulated datasets to verify a DC that can be used as a factor retention criterion for demonstrating its usefulness in a patient safety culture survey (PSC). Methods: Microsoft Excel Visual Basic for Applications was used to design a computer module for simulating 2000 datasets fitting the Rasch rating scale model. The datasets consisted of (i) five dual correlation coefficients (correl. = 0.3, 0.5, 0.7, 0.9, and 1.0) on two latent traits (i.e., true scores) following a normal distribution and responses to their respective 1/3 and 2/3 items in length; (ii) 20 scenarios of item lengths from 5 to 100; and (iii) 20 sample sizes from 50 to 1000. Each item containing 5-point polytomous responses was uniformly distributed in difficulty across a +/- 2 logit range. Three methods (i.e., dimension interrelation >= 0.7, Horn's parallel analysis (PA) 95% confidence interval, and individual random eigenvalues) were used for determining one factor to retain. DC refers to the binary classification (1 as one factor and 0 as many factors) used for examining accuracy with the indicators sensitivity, specificity, and area under receiver operating characteristic curve (AUC). The scale's reliability and DC were simultaneously calculated for each simulative dataset. PSC real data were demonstrated with DC to interpret reports of the unit-based construct validity using the author-made MS Excel module. Results: The DC method presented accurate sensitivity (=0.96), specificity (=0.92) with a DC criterion (=0.70), and AUC (=0.98) that were higher than those of the two PA methods. PA combined with DC yielded good sensitivity (=0.96), specificity (= 1.0) with a DC criterion (=0.70), and AUC (=0.99). Conclusions: Advances in computer technology may enable healthcare users familiar with MS Excel to apply DC as a factor retention criterion for determining a scale's unidimensionality and evaluating a scale's quality.
    關聯: Health and Quality of Life Outcomes, v.15, pp.2160-
    顯示於類別:[醫務管理系(所)] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML1085檢視/開啟
    s12955-017-0784-8.pdf1156KbAdobe PDF0檢視/開啟


    在CNU IR中所有的資料項目都受到原著作權保護.

    TAIR相關文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋