1000论坛币请问怎样用多个指标比较两种手术方式结果的好与差

请问一下高手，请问怎样用多个指标比较两种手术方式结果的好与差：
   我有100个病人，29个病人用A手术方式，71个用B手术方式，结果我用x1，x2，x3，x4，x5，x6，x7，x8指标反应每个病人手术后（不管是采用A方式还是采用B方式）的情况，现在我想知道：1.用怎样的统计方法进行统计；2.怎样用SAS程序比较出A与B哪一种手术方式好。3.可以用主成份分析或topsis分析解决我的问题吗？假设数据在附件中： 比较不同手术方式优劣.xls (22 KB)

2012-5-22 00:48:15 上传

（假设数值越大手术效果越好），谢谢各位高手了！！

如果看中文文献，CNKI上关于TOPSIS的就太多了。附件中有一篇文献给出了SAS宏。

TOPSIS sounds more proper here.

The idea of TOPSIS can be expressed in a series of steps.
(1) Obtain performance data for n alternatives over k criteria. Raw measurements are usually standardized, converting raw measures xij into standardized measures sij .
(2) Develop a set of importance weights wk, for each of the criteria. The basis for these weights can be anything, but, usually, is ad hoc re°ective of relative importance. Scale is not an issue if standardizing was accomplished in Step 1.
(3) Identify the ideal alternative (extreme performance on each criterion) s+;
(4) Identify the nadir alternative (reverse extreme performance on each criterion) s-;
(5) Develop a distance measure over each criterion to both ideal (D+) and nadir (D-).
(6) For each alternative, determine a ratio R equal to the distance to the nadir divided by the sum of the distance to the nadir and the distance to the ideal, R = D-/(D+ + D-)
(7) Rank order alternatives by maximizing the ratio in Step 6.

Thus, TOPSIS minimizes the distance to the ideal alternative while maximizing the distance to the nadir. There are a number of specific procedures that can be used for Step 2 (developing weights), and for Step 5 (distance measures). Additionally, different conventions can be applied to defining best performance (Step 3) and worst performance (Step 4).
A number of distance metrics can be applied. Traditional TOPSIS applied the Euclidean norm (minimization of square root of the sum of squared distances) to ideal and nadir solutions, a second power metric (P2). TOPSIS2 is a variant where distance was measured in least absolute value terms, a first power metric (P1). Another commonly used metric is the Tchebychev metric, where the minimum maximum difference is the basis for selection. This coincides with an infinite power-term (P1).

Thanks a lot! I need some time to understand your opinions。

这个问题我看着也很兴趣。期待楼主搞定了，再分享与我们

给你找来一些参考书

期望*****xyz能推荐一些相关的参考书，我可以去买！

这方面的东西我很感兴趣。今天先看一些中文文献，发现主要有以下几个问题：
1、作为决策变量的这么多X，如何客观地赋予其权重；
2、文献中的数据，一般是1个Y，多个X。要比较的是Y1，Y2，......Yn之间孰优孰劣。Y1，Y2，......Yn之间并没有重复。而楼主的Y乃是有重复的；
3、对于一般的TOPSIS，虽说用Excel手工计算就可以，但若有软件那是再好不过。目前已知DPS可以做TOPSIS，SAS的宏也可以，但不知是否还有其他更合适的软件？尤其是权重的科学选择与计算；以及Y具有重复的情形。

7楼厉i害，我的数据是有很多重复，原因是我想早点发帖，故写了一点数据后，其它数据是复制的，因为我想知道topsis方法，不知nkunku可否编写一个简单的topsis的sas程序，小弟感激不尽！！当然我会重新写上数据。或者可否先给几篇您今天看到的一些中文关于topsis的文章，谢谢！！

我上传一个刚找到的PPT，希望大家可以多提意见。还有，我在我找到的PPT未见topsis需要选择权重的计算方法，还望nkunku指导。