如何遍历参数进行分析 [英] How to iterate through parameters to analyse

问题描述

有没有更好的方法来迭代给定数据集的一组参数?显然，我试图得到一个相关系数表:列是CI、CVP、平均 PAP、平均 SAP"，行是ALAT、ASAT、GGT、Bili、LDH、FBG".对于每个组合，我想获得相关系数和显着性水平(p = ...).下面你会看到艰难的道路".但是有没有更优雅的方法，可能是一个可打印的表格?

Is there a better way to iterate through a set of parameters of a given dataset? Obviously, I try to get a table of correlation coefficients: columns are "CI, CVP, mean PAP, mean SAP", rows are "ALAT, ASAT, GGT, Bili, LDH, FBG". For each combination I´d like to get the correlation coefficient and the significance level (p=...). Below You see "the hard way". But is there a more elegant way, possibly with a printable table?

attach(Liver)
cor.test(CI, ALAT, method = "spearman")
cor.test(CI, ASAT, method = "spearman")
cor.test(CI, GGT, method = "spearman")
cor.test(CI, Bili, method = "spearman")
cor.test(CI, LDH, method = "spearman")
cor.test(CI, FBG, method = "spearman")

cor.test(CVP, ALAT, method = "spearman")
cor.test(CVP, ASAT, method = "spearman")
cor.test(CVP, GGT, method = "spearman")
cor.test(CVP, Bili, method = "spearman")
cor.test(CVP, LDH, method = "spearman")
cor.test(CVP, FBG, method = "spearman")

cor.test(meanPAP, ALAT, method = "spearman")
cor.test(meanPAP, ASAT, method = "spearman")
cor.test(meanPAP, GGT, method = "spearman")
cor.test(meanPAP, Bili, method = "spearman")
cor.test(meanPAP, LDH, method = "spearman")
cor.test(meanPAP, FBG, method = "spearman")

cor.test(meanSAP, ALAT, method = "spearman")
cor.test(meanSAP, ASAT, method = "spearman")
cor.test(meanSAP, GGT, method = "spearman")
cor.test(meanSAP, Bili, method = "spearman")
cor.test(meanSAP, LDH, method = "spearman")
cor.test(meanSAP, FBG, method = "spearman")

detach("Liver")

推荐答案

ltm库中有一个函数rcor.test()，可以制作相关系数表和p 值.例如使用的数据 iris 因为没有你的数据框.

There is a function rcor.test() in library ltm that makes table of correlation coefficients and p-values. For example used data iris as do not have your data frame.

library(ltm)
rcor.test(iris[,1:4],method="spearman")


             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length  *****       -0.167       0.882        0.834     
Sepal.Width   0.041        *****      -0.310       -0.289     
Petal.Length <0.001       <0.001       *****        0.938     
Petal.Width  <0.001       <0.001      <0.001        *****     

upper diagonal part contains correlation coefficient estimates 
lower diagonal part contains corresponding p-values

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