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Data X:
1 1 0 0 3.2 3.2 10.24 6 0 0 1 0 3.3 0 10.89 7 1 0 1 1 3.0 3 9 2 0 0 1 0 3.5 0 12.25 11 1 0 1 0 3.7 3.7 13.69 13 0 1 0 0 2.7 0 7.29 3 1 0 1 1 3.6 3.6 12.96 17 0 0 1 0 3.5 0 12.25 10 1 1 0 0 3.8 3.8 14.44 4 0 0 1 0 3.4 0 11.56 12 1 0 0 0 3.7 3.7 13.69 7 0 0 1 0 3.5 0 12.25 11 1 0 0 1 2.8 2.8 7.84 3 0 1 0 1 3.8 0 14.44 5 1 0 1 0 4.3 4.3 18.49 1 0 0 0 0 3.3 0 10.89 12 1 0 0 0 3.6 3.6 12.96 18 0 1 0 1 3.6 0 12.96 8 1 1 1 0 3.3 3.3 10.89 6 0 0 0 0 2.8 0 7.84 1
Names of X columns:
Geslacht Drugs Fruit Sport Gebgewicht Inter Gebgew2 Numeracy
R Code
library(corpcor) x <- t(y) (r1 <- pcor.shrink(x)) (r0 <- cor(x)) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Correlation Matrix',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('r0'),'</pre>',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable0.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Partial Pearson Correlation Matrix (Shrinkage Method)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste('<pre>',RC.texteval('r1'),'</pre>',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab')
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