| dc.contributor.advisor | 江振東 | zh_TW |
| dc.contributor.advisor | Chiang, Jeng-Tung | en_US |
| dc.contributor.author (Authors) | 劉佳鑫 | zh_TW |
| dc.contributor.author (Authors) | Benny Liu, Chia-Hsin | en_US |
| dc.creator (作者) | 劉佳鑫 | zh_TW |
| dc.creator (作者) | Benny Liu, Chia-Hsin | en_US |
| dc.date (日期) | 2000 | en_US |
| dc.date.accessioned | 31-Mar-2016 14:45:01 (UTC+8) | - |
| dc.date.available | 31-Mar-2016 14:45:01 (UTC+8) | - |
| dc.date.issued (上傳時間) | 31-Mar-2016 14:45:01 (UTC+8) | - |
| dc.identifier (Other Identifiers) | A2002001947 | en_US |
| dc.identifier.uri (URI) | https://ah.lib.nccu.edu.tw/item?item_id=92751 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 統計學系 | zh_TW |
| dc.description (描述) | 87354015 | zh_TW |
| dc.description.abstract (摘要) | 本文主要是在探討三個變數所構成之三維列聯表中，兩兩有序類別變數間的關係，而衡量的標準，我們則採用「兩兩變數所構成之二維列聯表中，相鄰兩列與相鄰兩行所求計出的相對成敗比（local odds ratios）」。在三維列聯表的資料架構下，我們可分別就固定某一變數水準之下兩個有序變數彼此間的「條件關係」，以及三個有序類別變數彼此兩兩間的「部分關係」，建構其各自的三維關係模型，並進行參數估計。此外，我們也提供必要的電腦程式，並舉出實例，加以說明。 | zh_TW |
| dc.description.abstract (摘要) | In analyzing a three-way contingency table with three ordinal variables, we can use association models suggested in Goodman (1979) to study the association between each pair of ordinal variables. The association was measured in terms of the local odds ratios formed from adjacent rows and adjacent columns of the cross-classification. This article investigates in great details the conditional association models and the partial association models for three-way cross-classifications. In addition, issues on estimating the para-meters in these two kinds of association models are discussed, and computer programs are provided. Some of the applications are illustrated. | en_US |
| dc.description.tableofcontents | 封面頁\n證明書\n致謝詞\n論文摘要\n目錄\n圖表目錄\n附錄目錄\n第一章 緒論\n1.1 研究緣起\n1.2 研究目的\n1.3 研究架構\n第二章 三維條件關係模型\n2.1 模型之基礎建構\n2.1.1 條件關係之相加效果模型（R＋C條件關係模型）\n2.1.2 條件關係之相乘效果模型（RC條件關係模型）\n2.2 模型之特例推衍\n2.2.1 固定性的條件關係模型\n2.2.1.1 組間異質模型\n2.2.1.2 組間同質模型\n2.2.2 單效果的條件關係模型\n2.2.2.1 組間異質模型\n2.2.2.2 簡單型組間異質模型\n2.2.2.3 組間同質模型\n2.2.3 雙效果的條件關係模型\n2.2.3.1 組間異質模型\n2.2.3.2 組間異質與組間同質兼具模型\n2.2.3.3 組間同質模型\n2.3 範例分析\n第三章 三維部分關係模型\n3.1 模型之基礎建構\n3.1.1 部分關係之相加效果模型\n3.1.2 部分關係之相乘效果模型\n3.2 模型之特例推衍\n3.2.1 固定性的部分關係模型\n3.2.2 單效果的部分關係模型\n3.2.3 雙效果的部分關係模型\n3.2.4 全效果的部分關係模型\n3.3 範例分析\n第四章 三維關係模型之參數估計\n4.1 三維條件關係模型\n4.1.1 最大概似函數\n4.1.2 參數估計的疊代規則\n4.1.3 類別參數估計值的中心化\n4.1.4 類別參數估計值的基準化\n4.1.5 參數估計的流程\n4.1.6 程式語法\n4.1.6.1 主程式\n4.1.6.2 核心副程式與附屬副程式\n4.1.6.3 輔助副程式與函數\n4.1.7 執行結果的比較\n4.1.8 程式使用說明\n4.2 三維部分關係模型\n4.2.1 最大概似函數\n4.2.2 參數估計的疊代規則\n4.2.3 類別參數估計值的中心化\n4.2.4 類別參數估計值的基準化\n4.2.5 參數估計的流程\n4.2.6 程式語法\n4.2.6.1 主程式\n4.2.6.2 核心副程式與附屬副程式\n4.2.6.3 輔助副程式與函數\n4.2.7 執行結果的比較\n4.2.8 程式使用說明\n第五章 實例分析\n5.1 三維條件關係模型\n5.2 三維部分關係模型\n第六章 結論與建議\n6.1 結論\n6.2 建議\n6.2.1 給一般使用者的建議\n6.2.2 給後續研究者的建議\n參考書目\n附錄 | zh_TW |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#A2002001947 | en_US |
| dc.subject (關鍵詞) | 有序分類 | zh_TW |
| dc.subject (關鍵詞) | 三維列聯表 | zh_TW |
| dc.subject (關鍵詞) | 對數相加性模型 | zh_TW |
| dc.subject (關鍵詞) | 對數相乘性模型 | zh_TW |
| dc.subject (關鍵詞) | 對數線性模型 | zh_TW |
| dc.subject (關鍵詞) | 非對數線性模型 | zh_TW |
| dc.subject (關鍵詞) | 條件關係 | zh_TW |
| dc.subject (關鍵詞) | 部分關係 | zh_TW |
| dc.subject (關鍵詞) | ordinal category | en_US |
| dc.subject (關鍵詞) | three-way contingency table | en_US |
| dc.subject (關鍵詞) | log-additive model | en_US |
| dc.subject (關鍵詞) | log-multiplicative model | en_US |
| dc.subject (關鍵詞) | log-linear model | en_US |
| dc.subject (關鍵詞) | non-loglinear model | en_US |
| dc.subject (關鍵詞) | conditional association | en_US |
| dc.subject (關鍵詞) | partial association | en_US |
| dc.title (題名) | 有序分類下三維列聯表之關係模型探討 | zh_TW |
| dc.title (題名) | On Association Models for Three-Way Contingency Tables with Ordinal Categories | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (參考文獻) | 01. Agresti, A. (1984). The Analysis of Ordinal Categorical Data. New York: John Wiley.\n02. Agresti, A. (1990). Categorical Data Analysis. New York: John Wiley.\n03. Agresti, A. (1996). An Introduction to Categorical Data Analysis. New York: John Wiley.\n04. Becker, M. P. (1990). Maximum likelihood estimation of the RC(M) association model. Applied Statistics, 39, 152-166.\n05. Becker, M. P. and C. C. Clogg (1989). Analysis of sets of two-way contingency tables using association models. Journal of the American Statistical Association, 84, 142-151.\n06. Clogg, C. C. (1982). Some models for the analysis of association in multi-way cross-classifications having ordered categories. Journal of the American Statistical Association, 77, 803-815.\n07. Clogg, C. C. and E. S. Shihadeh (1994). Statistical Models for Ordinal Variables. Thousand Oaks, California: Sage.\n08. Cody, R. P., and J. K. Smith (1997). Applied Statistics and the SAS Programming Language. Upper Saddle River, New Jersey: Prentice Hall.\n09. Davis, J. A. (1977). Codebook for the 1977 General Social Survey. Chicago: National Opinion Research Center.\n10. Dongarra, J. J., J. R. Bunch, C. B. Moler, and G. W. Stewart (1979). LINKPACK User’s Guide. Philadelphia: Society for Industrial and Applied Mathematics.\n11. Eliason, S. R. (1993). Maximum Likelihood Estimation: Logic and Practice. Newbury Park, California: Sage.\n12. Eliason, S. R. (1995). Two-way cross-classifications. Sociological Methods & Research, Vol. 24, No. 1, 30-67.\n13. Forthofer, R. N., and R. G. Lehnen (1981). Public Program Analysis, A New Catego-rical Data Approach. Belmont, California: Lifetime Learning Publications.\n14. Goodman, L. A. (1979). Simple models for the analysis of association in cross-classifications having ordered categories. Journal of the American Statistical Association, 74, 537-552.\n15. Goodman, L. A. (1984). The Analysis of Cross-Classified Data Having Ordered Cate-gories. Cambridge, Massachusetts: Harvard University Press.\n16. Nyhoff, L. R., and S. C. Leestma (1997). Fortran 90 for Engineers and Scientists. Upper Saddle River, New Jersey: Prentice Hall.\n17. 劉佳鑫、周國靖、鍾曉君合著，「校內公車滿意度調查」，國立政治大學統計學報第三十一期，台北：國立政治大學統計學系，頁1-25，民國八十九年。 | zh_TW |
