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| Title: | 有序分類下三維列聯表之關係模型探討
On Association Models for Three-Way Contingency Tables with Ordinal Categories |
| Authors: | 劉佳鑫
Benny Liu, Chia-Hsin |
| Contributors: | 江振東
Chiang, Jeng-Tung
劉佳鑫
Benny Liu, Chia-Hsin |
| Keywords: | 有序分類
三維列聯表
對數相加性模型
對數相乘性模型
對數線性模型
非對數線性模型
條件關係
部分關係
ordinal category
three-way contingency table
log-additive model
log-multiplicative model
log-linear model
non-loglinear model
conditional association
partial association |
| Date: | 2000 |
| Issue Date: | 2016-03-31 14:45:01 (UTC+8) |
| Abstract: | 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。
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. |
| Reference: | 01. Agresti, A. (1984). The Analysis of Ordinal Categorical Data. New York: John Wiley.
02. Agresti, A. (1990). Categorical Data Analysis. New York: John Wiley.
03. Agresti, A. (1996). An Introduction to Categorical Data Analysis. New York: John Wiley.
04. Becker, M. P. (1990). Maximum likelihood estimation of the RC(M) association model. Applied Statistics, 39, 152-166.
05. 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.
06. 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.
07. Clogg, C. C. and E. S. Shihadeh (1994). Statistical Models for Ordinal Variables. Thousand Oaks, California: Sage.
08. Cody, R. P., and J. K. Smith (1997). Applied Statistics and the SAS Programming Language. Upper Saddle River, New Jersey: Prentice Hall.
09. Davis, J. A. (1977). Codebook for the 1977 General Social Survey. Chicago: National Opinion Research Center.
10. 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.
11. Eliason, S. R. (1993). Maximum Likelihood Estimation: Logic and Practice. Newbury Park, California: Sage.
12. Eliason, S. R. (1995). Two-way cross-classifications. Sociological Methods & Research, Vol. 24, No. 1, 30-67.
13. Forthofer, R. N., and R. G. Lehnen (1981). Public Program Analysis, A New Catego-rical Data Approach. Belmont, California: Lifetime Learning Publications.
14. 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.
15. Goodman, L. A. (1984). The Analysis of Cross-Classified Data Having Ordered Cate-gories. Cambridge, Massachusetts: Harvard University Press.
16. Nyhoff, L. R., and S. C. Leestma (1997). Fortran 90 for Engineers and Scientists. Upper Saddle River, New Jersey: Prentice Hall.
17. 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。 |
| Description: | 碩士
國立政治大學
統計學系
87354015 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#A2002001947 |
| Data Type: | thesis |
| Appears in Collections: | [統計學系] 學位論文
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