Stare J, Harrell F E, Heinzl H
Department of Biomedical Informatics, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1104, Ljubljana, Slovenia.
Comput Methods Programs Biomed. 2001 Jan;64(1):45-52. doi: 10.1016/s0169-2607(00)00083-3.
Most researchers are familiar with ordinary multiple regression models, most commonly fitted using the method of least squares. The method of Buckley and James (J. Buckley, I. James, Linear regression with censored data, Biometrika 66 (1979) 429-436.) is an extension of least squares for fitting multiple regression models when the response variable is right-censored as in the analysis of survival time data. The Buckley-James method has been shown to have good statistical properties under usual regularity conditions (T.L. Lai, Z. Ying, Large sample theory of a modified Buckley-James estimator for regression analysis with censored data, Ann. Stat. 19 (1991) 1370-1402.). Nevertheless, even after 20 years of its existence, it is almost never used in practice. We believe that this is mainly due to lack of software and we describe here an S-Plus program that through its inclusion in a public domain function library fully exploits the power of the S-Plus programming environment. This environment provides multiple facilities for model specification, diagnostics, statistical inference, and graphical depiction of the model fit.
大多数研究人员都熟悉普通多元回归模型，最常用的是最小二乘法拟合。Buckley和James的方法（J. Buckley, I. James, Linear regression with censored data, Biometrika 66 (1979) 429 - 436.）是最小二乘法的一种扩展，用于在响应变量如生存时间数据分析中出现右删失时拟合多元回归模型。Buckley - James方法在通常的正则条件下已被证明具有良好的统计性质（T.L. Lai, Z. Ying, Large sample theory of a modified Buckley - James estimator for regression analysis with censored data, Ann. Stat. 19 (1991) 1370 - 1402.）。然而，即使它已经存在了20年，在实际应用中几乎从未被使用过。我们认为这主要是由于缺乏软件，在此我们描述一个S - Plus程序，通过将其包含在一个公共领域函数库中，充分利用了S - Plus编程环境的强大功能。这个环境为模型设定、诊断、统计推断以及模型拟合的图形描述提供了多种便利。
