Brenn T, Arnesen E
Stat Med. 1985 Oct-Dec;4(4):413-23. doi: 10.1002/sim.4780040403.
For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.
为了进行比较评估，我们使用判别分析、逻辑回归和Cox模型，在对6595名年龄在20至49岁之间的男性进行了9年随访后，选择全因死亡和冠心病死亡的风险因素。考虑了每1000人中死亡率在5至93之间的人群。判别分析选择的变量集与逻辑回归和Cox模型方法仅略有不同，而后两者总是选择相同的变量集。为逻辑回归和Cox模型选择提供的一种节省时间的选项，与判别分析相比并无优势。在分析超过3800名受试者时，逻辑回归和Cox模型方法分别比判别分析多消耗80倍和10倍的计算机时间。当在非逐步分析中纳入同一组变量时，所有方法估计的系数在大多数情况下几乎相同。总之，对于初步或逐步分析，提倡使用判别分析，否则应使用Cox模型方法。
