?cor says that cor() can be applied to
'numeric vector, matrix or data frame'
?cor.test requires
'numeric vectors of data values'
So, what's your q?
As to na.action:
?cor.test makes no reference to na.action for the default method.
Looking at the code of cor.test.default shows that only complete
cases are used. The formula method does have an argument na.action
and it works just fine for me.
Try getOption('na.action') and you'll probably find that it is set
^^^^^^
to 'na.omit'.
-Peter Ehlers
Godmar Back wrote:
Hi,
I am trying to use R for some survey analysis, and need to compute the
significance of some correlations. I read the man pages for cor and
cor.test, but I am confused about
- whether these functions are intended to work the same way
- about how these functions handle NA values
- whether cor.test supports 'use = complete.obs'.
Some example output may explain why I am confused:
-----------------------------------------------
WORKS:
cor(q[[9]], q[[10]])
perceivedlearningcurve
overallimpression 0.7440637
-----------------------------------------------
DOES NOT WORK:
cor.test(q[[9]], q[[10]])
Error in `[.data.frame`(x, OK) : undefined columns selected
-----------------------------------------------
(I assume that's because of R's generous type coercions.... does R
have a "typeof" operator to learn what the type of q[[9]] is?)
-----------------------------------------------
WORKS:
cor.test(q[[9]][,1], q[[10]][,1])
Pearson's product-moment correlation
data: q[[9]][, 1] and q[[10]][, 1]
t = 12.9877, df = 136, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.6588821 0.8104055
sample estimates:
cor
0.7440637
-----------------------------------------------
WORKS, but propagates NAs:
cor(q[[9]], q[[51]])
usefulnessautodetectionbox_ord
overallimpression NA
-----------------------------------------------
WORKS, and uses complete observations only
cor(q[[9]], q[[51]], use="complete.obs")
usefulnessautodetectionbox_ord
overallimpression 0.2859895
-----------------------------------------------
WORKS, apparently, but does not require 'use="complete.obs"' (!?)
cor.test(q[[9]][,1], q[[51]][,1])
Pearson's product-moment correlation
data: q[[9]][, 1] and q[[51]][, 1]
t = 3.1016, df = 108, p-value = 0.002456
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.1043351 0.4491779
sample estimates:
cor
0.2859895
-----------------------------------------------
The help page for cor.test states that 'getOption('na.action')'
describes the action taken on NAs:
getOption("na.option")
NULL
-----------------------------------------------
No action is taken, yet cor.test appears to only use complete observations (!?)
Others believe that cor.test accepts 'use=complete.obs':
http://markmail.org/message/nuzqeouqhbb7f6ok
--------------
Needless to say, this makes writing robust code very hard.
I'm wondering what the rationale for the inconsistencies between cor
and cor.test is.
Thanks!
- Godmar
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and provide commented, minimal, self-contained, reproducible code.
