R help - Oct 2010 - S: appropriate significance tests

Hello

(1) How can I compare two Pearson correlation coefficients for significant
differences without the use of the raw data?

(2) How can I compare two linear regression coefficients for significant
differences without the use of the raw data?

(3) How can I compare two multiple correlation coefficients (as produced in a
linear regression) for significant differences, again, if the raw data should
not be used?

<src type="perhaps useful">
da <- data.frame(
  "y1"=sample(1:5, 40, repl=T),
  "y2"=sample(1:5, 40, repl=T),
  "x1"=sample(1:5, 40, repl=T),
  "x2"=sample(1:5, 40, repl=T)
)
cro1 <- cor(da$y1, da$x1)
cro2 <- cor(da$y2, da$x1)
lmo1 <- lm(y1 ~ x1 + x2, data=da)
lmo2 <- lm(y2 ~ x1 + x2, data=da)
</src>

Thanks, S?ren

It is not completely clear what question you are trying to answer or what you
are trying to accomplish.  But here are some additional questions that may help:

What tests would you use if you could use the original data?
What assumptions are you willing to make about the data and/or statistics?
What are you trying to accomplish?

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of soeren.vogel at eawag.ch
> Sent: Wednesday, October 20, 2010 7:33 AM
> To: r-help at r-project.org
> Subject: [R] S: appropriate significance tests
> 
> Hello
> 
> (1) How can I compare two Pearson correlation coefficients for
> significant differences without the use of the raw data?
> 
> (2) How can I compare two linear regression coefficients for
> significant differences without the use of the raw data?
> 
> (3) How can I compare two multiple correlation coefficients (as
> produced in a linear regression) for significant differences, again, if
> the raw data should not be used?
> 
> <src type="perhaps useful">
> da <- data.frame(
>   "y1"=sample(1:5, 40, repl=T),
>   "y2"=sample(1:5, 40, repl=T),
>   "x1"=sample(1:5, 40, repl=T),
>   "x2"=sample(1:5, 40, repl=T)
> )
> cro1 <- cor(da$y1, da$x1)
> cro2 <- cor(da$y2, da$x1)
> lmo1 <- lm(y1 ~ x1 + x2, data=da)
> lmo2 <- lm(y2 ~ x1 + x2, data=da)
> </src>
> 
> Thanks, S?ren
> 
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