# Q lower p-value or narrower CI the better

9 views

### Cosine

Jan 11, 2022, 1:22:04 PMJan 11
to
Hi:

When doing a statistical test, we often compute the p-value and confidence interval (CI) at a given significance level of alpha.

Questions arise: would it be better to have a lower p-value? Likewise, would it be better to have a narrower CI? Why and why not?

Thanks,

### Rich Ulrich

Jan 11, 2022, 2:34:31 PMJan 11
to
On Tue, 11 Jan 2022 10:22:02 -0800 (PST), Cosine <ase...@gmail.com>
wrote:

>Hi:
>
> When doing a statistical test, we often compute the p-value and confidence interval (CI) at a given significance level of alpha.
>
> Questions arise: would it be better to have a lower p-value? Likewise, would it be better to have a narrower CI? Why and why not?
>

Cost. And your friends may make fun of you if you spend too much.

I want a car that has great acceleration and top speed and outstanding
fuel economical. It should also be roomy and fun to drive. It should
look good. Especiallly, it should be cheap to buy and to insure.

Unfortunate, that dream. Buying, I've always settled for a limited
choice among "what's available" and what is convenient.

--
Rich Ulrich

### Cosine

Jan 11, 2022, 10:10:25 PMJan 11
to
Cosine 在 2022年1月12日 星期三上午2:22:04 [UTC+8] 的信中寫道：
> Hi:
>
> When doing a statistical test, we often compute the p-value and confidence interval (CI) at a given significance level of alpha.
>
> Questions arise: would it be better to have a lower p-value? Likewise, would it be better to have a narrower CI? Why and why not?
>

For p-value, suppose we have two new diagnostic methods, A and B. We want to know:
1) are they both better than the standard method?
2) is method A better than B?

We desing studies and use the accuracy (Acc) to check the performances.

By comparing the methods A and the standard one, we have: Acc_Asmp, p-value_A, CI_A
B Acc_Bsmp, p-value_B, CI_B

If p-value_A < p-value_B, could we say that Acc_Asmp is more significant than Acc_Bsmp?

Similarly, we define the width of CI as WCI. We have WCI_A and WCI_B.

If WCI_A < WCI_B, could we say that Acc_A is more significant or more reliable, since
we could be sure that the true value of Acc_A would fall in a narrower CI (smaller width)?

### Rich Ulrich

Jan 13, 2022, 8:24:29 PMJan 13
to
On Tue, 11 Jan 2022 19:10:23 -0800 (PST), Cosine <ase...@gmail.com>
wrote:

>Cosine ? 2022?1?12? ?????2:22:04 [UTC+8] ??????
>> Hi:
>>
>> When doing a statistical test, we often compute the p-value and confidence interval (CI) at a given significance level of alpha.
>>
>> Questions arise: would it be better to have a lower p-value? Likewise, would it be better to have a narrower CI? Why and why not?
>>
>
>For p-value, suppose we have two new diagnostic methods, A and B. We want to know:
>1) are they both better than the standard method?
>2) is method A better than B?

I think you want to mull the idea that TESTing is separate
from ESTIMATION. Testing starts by designating a cutoff.
Estimation reports "effect sizes" -- usually, in natural units of the
experiment, rather than by comparing p-values.

Yeah, I know that if tests are entirely commensurate (same Ns,
SDs,), then I know that a p= 0.001 reflects a t-test mean-difference
which is about twice that for p= 0.05. I would only ever mention
the comparisosn if I were already engaged in explaining "effect
sizes" in a more thorough way, such as "Why we should ignore
all the 'tiny' effects where p is not < 0.001."

And this statement of yours is not the way statisticians ever discuss
either -- "For p-value, suppose we have ....".

I assume that you intended to say something like, "For two new
diagnostic methods, we have tests (with p-values) comparing each
to a standard and also to each other."

In a testing environment, or when one is TALKing about testing,
we never would ASSERT that A is better than B unless the test
for A vs B has a p-value meets the cutoff that was designated.

>
> We desing studies and use the accuracy (Acc) to check the performances.
>
> By comparing the methods A and the standard one, we have: Acc_Asmp, p-value_A, CI_A
> B Acc_Bsmp, p-value_B, CI_B
>
> If p-value_A < p-value_B, could we say that Acc_Asmp is more significant than Acc_Bsmp?
>
> Similarly, we define the width of CI as WCI. We have WCI_A and WCI_B.
>
> If WCI_A < WCI_B, could we say that Acc_A is more significant or more reliable, since
> we could be sure that the true value of Acc_A would fall in a narrower CI (smaller width)?

--
Rich Ulrich