Hello,
You can write a function to compute the scores:
z_score <- function(x, beta = mean, beta0 = 0){
beta <- match.fun(beta)
n <- length(x)
score <- sqrt(n)*(beta(x) - beta0)/sd(x)
names(score) <- if(n < 30) "t.score" else "z.score"
score
}
# data example
x <- rt(20, df = 1)
tt <- t.test(x)
pvals <- tt$p.value
# Now compare these 3 results and see if it answers the question
qt(pvals/2, 19, lower.tail = F)
tt$statistic
z_score(x)
Hope this helps,
Rui Barradas
Às 15:40 de 06/05/20, Ana Marija escreveu:
I guess I can have
z-score=Beta/StdErr
On Wed, May 6, 2020 at 9:37 AM Ana Marija <sokovic.anamar...@gmail.com> wrote:
thanks, can you please tell em what would be the way not to get the
absolute (always positive values)
On Wed, May 6, 2020 at 9:33 AM Rui Barradas <ruipbarra...@sapo.pt> wrote:
Hello,
Sorry but after reading my answer I believe it's not completely clear.
I meant absolute values, the actual t-scores as computed from the data
might be negative. Your code will always produce positive numbers.
Hope this helps,
Rui Barradas
Às 15:27 de 06/05/20, Rui Barradas escreveu:
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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