Wan J Y, Wang W, Bromberg J
Division of Biostatistics and Epidemiology, University of Tennessee, Memphis 38163, USA.
Comput Methods Programs Biomed. 1994 Dec;45(4):307-10. doi: 10.1016/0169-2607(94)01591-3.
In this paper, a SAS macro is described for calculating the likelihood of the 'saturated' model in the analysis of ordinal regression. The outcome variable is multinomial on an ordinal scale, while the explanatory variables can be nominal or ordinal. Several ordinal regression models may be fitted to the data. One method of testing for the goodness of fit of these regression models is by comparing the residual deviance with the chi 2 distribution. In SAS, PROC LOGISTIC may be used to fit this type of data with proportional odds model. Unfortunately, the residual deviance is not available from the output. Our SAS macro will supplement the SAS output so that the residual deviance test may be carried out. The data from an ongoing HIV study is used as an illustration.
本文描述了一个SAS宏，用于在有序回归分析中计算“饱和”模型的似然性。结果变量在有序尺度上是多项的，而解释变量可以是名义变量或有序变量。可以对数据拟合多个有序回归模型。检验这些回归模型拟合优度的一种方法是将残差离差与卡方分布进行比较。在SAS中，可以使用PROC LOGISTIC用比例优势模型拟合这类数据。不幸的是，输出中没有残差离差。我们的SAS宏将补充SAS输出，以便可以进行残差离差检验。以一项正在进行的HIV研究的数据为例进行说明。
