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pcor
2012 Apr 18
0
Text mining: Narrowing a field of 27, 855 predictors using semi-partial correlations or some other means
...significant in the actual data mining.
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Is this likely to be a good approach? Or is there likely to be a better way of doing it?
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If it is a good approach, I?m wondering how to go about obtaining the necessary results. I?ve managed to figure out how to compute semi-partial correlations using the spcor.test() function in the ppcor package, as in:
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> spcor.test(as.numeric(Tested$TestStatus=="Yes"), Tested$predictor, Tested $nchar_record)
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?? estimate????? p.value statistic?? n gp? Method
1 0.3853547 2.307562e-08? 5.587203 182? 1 pearson
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This is fine for a single pair of variables....
2013 May 08
0
PPCOR: Semipartial Correlation & Regression weights
...ata <- na.omit(data1)
In the following example, I am interested in the regression
coefficient/semi-partial correlation of s1(x) and WSAS01 (y).
Regression:
m1 <- lm(WSAS01 ~ s1+s2+s3+s5+s10+age, data=data)
summary(m1)
regression coefficient s1: 0.091
Semipartial Correlation:
library(ppcor)
spcor.test(data$s1,data$WSAS01,data[,c("age","s2","s3","s5","s10")])
semi-partial correlation s1 with WSAS01: 0.202
What am I doing wrong?
Thank you
T
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