學術產出-Theses
Article View/Open
Publication Export
-
題名 單一總體尺度及多項評估的合意度分析
Agreement analysis between a single global scale and multi‐item assessments作者 顏柏魁 貢獻者 鄭宗記
顏柏魁關鍵詞 期望最大演算法
隨機差異
位置分布系統差異
位置集中系統差異
單調合意度係數
加總尺度
因素分析
多序類相關係數
非線性主成分分析日期 2013 上傳時間 29-Jul-2014 16:03:07 (UTC+8) 摘要 實務上，不完整資料為常見的問題，對於遺漏值的處理方式，分成刪除法或填補法這兩種方法，而面對問卷類型的資料，通常採用順序尺度變數當作問卷的評分標準，本篇使用EM方法填補遺漏值，由於順序尺度變數時常發生樣本數可能沒有遠大於問卷之題目組成的列聯表格子數，導致EM無法執行，因此逐次對資料執行EM填補遺漏值。藉由EM填補後的完整資料使用加總尺度、因素分析和非線性主成分分析整合為單一總體尺度，應用等級轉換法將單一總體尺度轉換為順序尺度，接著評估兩順序尺度變數之間合意度。 參考文獻 Carroll, J. B. (1961). The nature of the data, or how to choose a correlation coefficient. Psychometrika, 26(4), 347-372.Chen, T., & Fienberg, S. E. (1974). Two-dimensional contingency tables with both completely and partially cross-classified data. Biometrics, 629-642.3104-3117.De Leeuw, J., & Mair, P. (2009). Gifi methods for optimal scaling in R: The package homals. Journal of Statistical Software, forthcoming, 1-30.DiStefano, C., Zhu, M., & Mindrila, D. (2009). Understanding and using factor scores: Considerations for the applied researcher. Practical Assessment, Research & Evaluation, 14(20), 1-11.Everitt, B., & Hothorn, T. (2011). An introduction to applied multivariate analysis with R. Springer.Fuchs, C. (1982). Maximum likelihood estimation and model selection in contingency tables with missing data. Journal of the American Statistical Association, 77(378), 270-278.Fayers, P., & Machin, D. (2007). Quality of life: the assessment, analysis and interpretation of patient-reported outcomes. John Wiley & Sons.Gifi, A. (1990). Homogeneity analysis. Nonlinear multivariate analysis. Chichester: John Wiley & Sons. Hochberg, Y. (1977). On the use of double sampling schemes in analyzing categorical data with misclassification errors. Journal of the American Statistical Association, 72(360a), 914-921.Kuroda, M., Mori, Y., Masaya, I., & Sakakihara, M. Alternating least squares in nonlinear prin-cipal components.Little, R. J., & Rubin, D. B. (1989). The analysis of social science data with missing values. Sociological Methods & Research, 18(2-3), 292-326.Olsson, U. (1979). Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika, 44(4), 443-460.Svensson, E. (2000). Comparison of the quality of assessments using continuous and discrete ordinal rating scales. Biometrical Journal, 42(4), 417-434.Svensson, E., & Holm, S. (1994). Separation of systematic and random differences in ordinal rating scales. Statistics in medicine, 13(23‐24), 2437-2453.Schafer, J. L. (2010). Analysis of incomplete multivariate data. CRC press.Svensson, E. (2012). Different ranking approaches defining association and agreement measures of paired ordinal data. Statistics in medicine, 31(26), 3104-3117.Tallis, G. M. (1962). The maximum likelihood estimation of correlation from contingency tables. Biometrics, 18(3), 342-353.Uebersax, J. S. (2006). The tetrachoric and polychoric correlation coefficients.Statistical methods for rater agreement web site, 2006. 描述 碩士
國立政治大學
統計研究所
101354020
102資料來源 http://thesis.lib.nccu.edu.tw/record/#G0101354020 資料類型 thesis dc.contributor.advisor 鄭宗記 zh_TW dc.contributor.author (Authors) 顏柏魁 zh_TW dc.creator (作者) 顏柏魁 zh_TW dc.date (日期) 2013 en_US dc.date.accessioned 29-Jul-2014 16:03:07 (UTC+8) - dc.date.available 29-Jul-2014 16:03:07 (UTC+8) - dc.date.issued (上傳時間) 29-Jul-2014 16:03:07 (UTC+8) - dc.identifier (Other Identifiers) G0101354020 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/67859 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 統計研究所 zh_TW dc.description (描述) 101354020 zh_TW dc.description (描述) 102 zh_TW dc.description.abstract (摘要) 實務上，不完整資料為常見的問題，對於遺漏值的處理方式，分成刪除法或填補法這兩種方法，而面對問卷類型的資料，通常採用順序尺度變數當作問卷的評分標準，本篇使用EM方法填補遺漏值，由於順序尺度變數時常發生樣本數可能沒有遠大於問卷之題目組成的列聯表格子數，導致EM無法執行，因此逐次對資料執行EM填補遺漏值。藉由EM填補後的完整資料使用加總尺度、因素分析和非線性主成分分析整合為單一總體尺度，應用等級轉換法將單一總體尺度轉換為順序尺度，接著評估兩順序尺度變數之間合意度。 zh_TW dc.description.tableofcontents 第一章 研究動機 7第二章 文獻回顧 9第一節 不完整類別變數資料處理 9第二節 單一總體尺度 13第三節 評估順序尺度的變數合意度 18第三章 實證分析 29第一節 不完整資料的敘述統計 29第二節 EM填補遺漏值 32第三節 單一總體尺度與合意度評估 36第四章 模擬研究 49第一節 5%遺漏比例 50第二節 10%遺漏比例 52第三節 15%遺漏比例 54第五章 結論 57 zh_TW dc.format.extent 1146808 bytes - dc.format.mimetype application/pdf - dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0101354020 en_US dc.subject (關鍵詞) 期望最大演算法 zh_TW dc.subject (關鍵詞) 隨機差異 zh_TW dc.subject (關鍵詞) 位置分布系統差異 zh_TW dc.subject (關鍵詞) 位置集中系統差異 zh_TW dc.subject (關鍵詞) 單調合意度係數 zh_TW dc.subject (關鍵詞) 加總尺度 zh_TW dc.subject (關鍵詞) 因素分析 zh_TW dc.subject (關鍵詞) 多序類相關係數 zh_TW dc.subject (關鍵詞) 非線性主成分分析 zh_TW dc.title (題名) 單一總體尺度及多項評估的合意度分析 zh_TW dc.title (題名) Agreement analysis between a single global scale and multi‐item assessments en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) Carroll, J. B. (1961). The nature of the data, or how to choose a correlation coefficient. Psychometrika, 26(4), 347-372.Chen, T., & Fienberg, S. E. (1974). Two-dimensional contingency tables with both completely and partially cross-classified data. Biometrics, 629-642.3104-3117.De Leeuw, J., & Mair, P. (2009). Gifi methods for optimal scaling in R: The package homals. Journal of Statistical Software, forthcoming, 1-30.DiStefano, C., Zhu, M., & Mindrila, D. (2009). Understanding and using factor scores: Considerations for the applied researcher. Practical Assessment, Research & Evaluation, 14(20), 1-11.Everitt, B., & Hothorn, T. (2011). An introduction to applied multivariate analysis with R. Springer.Fuchs, C. (1982). Maximum likelihood estimation and model selection in contingency tables with missing data. Journal of the American Statistical Association, 77(378), 270-278.Fayers, P., & Machin, D. (2007). Quality of life: the assessment, analysis and interpretation of patient-reported outcomes. John Wiley & Sons.Gifi, A. (1990). Homogeneity analysis. Nonlinear multivariate analysis. Chichester: John Wiley & Sons. Hochberg, Y. (1977). On the use of double sampling schemes in analyzing categorical data with misclassification errors. Journal of the American Statistical Association, 72(360a), 914-921.Kuroda, M., Mori, Y., Masaya, I., & Sakakihara, M. Alternating least squares in nonlinear prin-cipal components.Little, R. J., & Rubin, D. B. (1989). The analysis of social science data with missing values. Sociological Methods & Research, 18(2-3), 292-326.Olsson, U. (1979). Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika, 44(4), 443-460.Svensson, E. (2000). Comparison of the quality of assessments using continuous and discrete ordinal rating scales. Biometrical Journal, 42(4), 417-434.Svensson, E., & Holm, S. (1994). Separation of systematic and random differences in ordinal rating scales. Statistics in medicine, 13(23‐24), 2437-2453.Schafer, J. L. (2010). Analysis of incomplete multivariate data. CRC press.Svensson, E. (2012). Different ranking approaches defining association and agreement measures of paired ordinal data. Statistics in medicine, 31(26), 3104-3117.Tallis, G. M. (1962). The maximum likelihood estimation of correlation from contingency tables. Biometrics, 18(3), 342-353.Uebersax, J. S. (2006). The tetrachoric and polychoric correlation coefficients.Statistical methods for rater agreement web site, 2006. zh_TW
