Hello,
Another option is to use stats::t.test
t.test(x)$statistic
Or, if you want to test against a beta0 != 0,
t.test(x, mu = beta0)$statistic
But in this case the estimator is the estimator for the mean value.
Hope this helps,
Rui Barradas
Às 15:54 de 06/05/20, Ana Marija escreveu:
Thanks Patrick, so in conclusion this is fine?
z-score=Beta/StdErr
On Wed, May 6, 2020 at 9:52 AM Patrick (Malone Quantitative)
<[email protected]> wrote:
Guessing for Ana, but no, that's a different meaning. Beta/StdErr is a
z statistic--a test statistic against (usually) the tails of the unit
normal distribution. So like a t-test with infinite df.
On Wed, May 6, 2020 at 10:41 AM Rui Barradas <[email protected]> wrote:
Hello,
By z-scores do you mean function help('scale')?
Hope this helps,
Rui Barradas
Às 15:31 de 06/05/20, Ana Marija escreveu:
Hi Rui,
Thank you for getting back to me. Is there is a better way to
calculate Z scores if I have p values, SE and Beta?
Thanks
Ana
On Wed, May 6, 2020 at 9:27 AM Rui Barradas <[email protected]> wrote:
Hello,
That gives the *absolute* t-scores. If it's all you need/want, then the
answer is yes, you can.
Hope this helps,
Rui Barradas
Às 14:28 de 06/05/20, Ana Marija escreveu:
Hello,
Can I apply the quantile function qt() this way?
qt(pvals/2, 406-34, lower.tail = F)
to get the T-scores?
Thanks
Ama
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______________________________________________
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--
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