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RE: st: RE: joint significant
No. You reject the null when the p-value is less than the set
confidence criterion. You fail to reject the null when the p-value is
greater than the set confidence criterion.
Examples:
P-value = 0.0890
Confidence criterion
0.10 = 90%
0.05 = 95%
0.01 = 99%
At a 90% confidence level, you would reject the null b/c 0.0890 < 0.10
At a 95% confidence level, you would fail to reject the null b/c 0.0890
> 0.05
At a 99% confidence level, you would fail to reject the null b/c 0.0890
> 0.01
You can establish you own confidence level by subtracting the p-value
from 1.
If the p-value is less than the confidence criterion, then you reject
the null. If the p-value is greater than the confidence criterion, then
you fail to reject the null.
Justin White
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Joanne
Marshall
Sent: Tuesday, January 16, 2007 1:38 PM
To: [email protected]
Subject: RE: st: RE: joint significant
Hi again Justin,
also I have just noticed something. if my p value is 0.089, at 95%
level,
(0.05 p value), shouldnt we reject the null (HO) because 0.089> 0.05. I
thought we would fail to reject the null if our p value is smaller than
the
95% p value (0.05)
Cheers Jo
>From: "White, Justin" <[email protected]>
>Reply-To: [email protected]
>To: <[email protected]>
>Subject: RE: st: RE: joint significant
>Date: Tue, 16 Jan 2007 13:26:05 -0500
>
>The H0 is the null hypothesis and H1 is the alternative hypothesis.
>Sometimes the notation can be different. It can be H0 is the null and
>Ha is the alternative. I always thought the H0 and Ha notation was
more
>intuitive than the H0 and H1.
>
>In this case, the null hypothesis (H0) is B2=B3=B4=0.
>The alternative hypothesis (H1) is the estimated coefficients (Bi) are
>not jointly equal to zero.
>
>Therefore, if you reject the null, you automatically accept the
>alternative which means the estimated coefficients are jointly
>significantly different from zero.
>
>If the fail to reject the null, then you are effectively accepting the
>null to be true and the estimated coefficients are jointly
>insignificantly different from zero.
>
>The joint test is different from the variable-specific test (T-test).
>Just because the F-test tells us that the variables are jointly
>different from zero does not imply that all of the estimated
>coefficients are different from zero independently. You use a T-test
to
>determine the significance of an individual variable and use the F-test
>for joint tests.
>
>I hope this helps.
>
>
>
>Justin White
>
>-----Original Message-----
>From: [email protected]
>[mailto:[email protected]] On Behalf Of Joanne
>Marshall
>Sent: Tuesday, January 16, 2007 1:14 PM
>To: [email protected]
>Subject: RE: st: RE: joint significant
>
>Dear Justin,
>
>Thank you for making such a clear statment on the test and my result. I
>now
>understand much more than I did, and that was a much better explanation
>than
>my textbook gives!
>
>Regarding the null hypothesis, is that equivalent to H1? I always
>confused
>my H0 and H1.
>
>h0=null= estimated coefficients are jointly insignificantly different
>from
>zero. (b2=b3=b4=0)
>ho= estimated coefficients are not jointly insignificantly different
>from
>zero. (b2 not equal to b3... not equal to b4/0
>
>or is it the other way round?
>
>Thank you for your time and patience. I am finally getting this!
>
>Cheers Jo
>
>
>
> >From: "White, Justin" <[email protected]>
> >Reply-To: [email protected]
> >To: <[email protected]>
> >Subject: RE: st: RE: joint significant
> >Date: Tue, 16 Jan 2007 12:51:40 -0500
> >
> >The 91% confidence level comes from the p-value given in the Wald
test.
> >
> >
> >Here is how to interpret a p-value. Let's say you have a p-value of
> >0.0890 from an F-test. This tells us that given the data sample, we
>can
> >expect the estimated coefficients to be jointly equal to zero in 8.9
> >times out of 100. This is known as Type-1 error. If you are using a
> >confidence criterion of 95%, you are only willing to make a Type-1
>error
> >in 5 out of 100 times. Therefore, a confidence level of 91.1% falls
> >outside of your confidence criteria and you would fail to reject the
> >null. This means the estimated coefficients are jointly
>insignificantly
> >different from zero.
> >
> >If you are using a 95% confidence level, then you want a p-value that
>is
> >less than or equal to 0.05. The smaller the p-value, the less likely
> >you are to make a Type-1 error. You get the confidence level by
> >subtracting the p-value from one (1-0.0890 = 0.0911 = 91.1%)
> >
> >This would be the statement(s) you would make.....
> >Based on a confidence level of 95%, I would fail to reject the null
> >hypothesis that the estimated coefficients are jointly equal to zero.
> >
> >Or
> >
> >Based on a confidence level of 90%, I would reject the null
hypothesis
> >that the estimated coefficients are jointly equal to zero.
> >
> >Or
> >
> >I reject the null hypothesis that the estimated coefficients are
>jointly
> >equal to zero at a confidence level of 91.1%.
> >
> >Hope this helps.
> >
> >
> >Justin White
> >
> >
> >-----Original Message-----
> >From: [email protected]
> >[mailto:[email protected]] On Behalf Of Joanne
> >Marshall
> >Sent: Tuesday, January 16, 2007 12:31 PM
> >To: [email protected]
> >Subject: RE: st: RE: joint significant
> >
> >Thank you, Justin.
> >
> >"Assuming you have a 95% confidence level criterion, you will fail to
> >reject the null hypothesis that the estimated coefficients are
jointly
> >equal to zero with a confidence level of 91%."
> >
> >How can you tell we reject the null though hypothesis and where is
the
> >91%
> >from?
> > > F( 1, 538) = 2.1
> > > Prob > F = 0.0890
> >
> >the p value is 0.0890, which is bigger than 0.05 therefore we reject
>the
> >
> >null.
> >i am using 0.05 as the p value because it is 95% confidnece level
> >criterion.
> >is this correct?
> >thank you.
> >
> >Cheers Jo
> >
> > >From: "White, Justin" <[email protected]>
> > >Reply-To: [email protected]
> > >To: <[email protected]>
> > >Subject: st: RE: joint significant
> > >Date: Tue, 16 Jan 2007 12:23:19 -0500
> > >
> > >The Wald Test is a joint significance test. It depends on how you
>set
> > >up the test if you want to determine if a specific coefficient has
>the
> > >appropriate sign. The results you included tell us:
> > >
> > >Assuming you have a 95% confidence level criterion, you will fail
to
> > >reject the null hypothesis that the estimated coefficients are
>jointly
> > >equal to zero with a confidence level of 91%.
> > >
> > >There is no need to use an F-table. The p-value given in the test
> >tells
> > >you the level of confidence. As one of my professors told me
> > >"statistical tables are for luddites".
> > >
> > >
> > >Hope this helps.
> > >
> > >
> > >Justin White
> > >
> > >-----Original Message-----
> > >From: [email protected]
> > >[mailto:[email protected]] On Behalf Of Joanne
> > >Marshall
> > >Sent: Tuesday, January 16, 2007 12:15 PM
> > >To: [email protected]
> > >Subject: st: joint significant
> > >
> > >Dear Stata fellow,
> > >
> > >If the result which I have worked out is for a joint sign test
(Wald
> > >test)
> > >
> > > F( 1, 538) = 2.1
> > > Prob > F = 0.0890
> > >
> > >how can I tell if this is jointly significant or not? do I look at
> > >0.0790 or
> > >3.10 as F observ to compare with my F crit. Also from the stat.
>table,
> > >do I
> > >look for F crit under (1,538) at my desirable level on significance
>or
> > >others?
> > >
> > >Cheers
> > >Jo
> > >
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_________________________________________________________________
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