TY - JOUR JF - srtc-jsri JO - JSRI VL - 1 IS - 1 PY - 2004 Y1 - 2004/9/01 TI - Modeling Paired Ordinal Response Data TT - مدل‌سازی پاسخ‌های زوج شده‌ی رتبه‌ای N2 - About 25 years ago, McCullagh proposed a method for modeling univariate ordinal responses. After publishing this paper, other statisticians gradually extended his method, such that we are now able to use more complicated but efficient methods to analyze correlated multivariate ordinal data, and model the relationship between these responses and host of covariates. In this paper, we aim to present the recent progressions in modeling ordinal response data, especially in bivariate ordinal responses that arise from medical studies relating to paired organs such as ophthalmology, otology, nephrology etc. Additionally, we present a new model for analyzing correlated ordinal response data. This model is an appropriate alternative for bivariate cumulative probit regression model, when joint distribution of response data is not symmetric. Finally, as an applied example, we analyze the obtained data from an epidemiologic study relating to periodontal status among high school students in Tehran using this method and compare the results with the similar models. SP - 51 EP - 68 AU - Kazemnejad, Anoshiravan AU - Zayeri, Farid AD - KW - Correlated ordinal responses KW - bivariate latent distribution KW - generalized estimating equations KW - generalized linear models. UR - http://jsri.srtc.ac.ir/article-1-139-en.html DO - 10.18869/acadpub.jsri.1.1.51 ER -