If your E is a constant, it has no variance, so the sampling distribution of the sampling mean has no variance either: the standard error in the sample divided by square root of N would always evaluate to zero. So any ttest for anything other than the constant value of E would inevitably lead to a rejection.
Martin Weiss
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-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Ngoc Anh Vo Thi
Sent: Friday, May 23, 2008 11:17 AM
To: Statalist
Subject: st: missing p-value from t-test
Dear stata-users,
My appologies for a beginner’s question. I’m estimating the following model using OLS:
lnROA=alpha + beta(1)*lnW(1) + beta(2)*lnW(2) + beta(3)*lnW(3) + gamma*D + epsilon.
Then I calculate an E statistic that equals the sum of beta(1), beta(2), and beta(3). I want to test whether E=0, using a t-test:
ttest E==0
One-sample t test
------------------------------------------------------------------------------
Variable | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
---------+--------------------------------------------------------------------
E_CZE_B | 38 -.0550183 0 0 -.0550183 -.0550183
------------------------------------------------------------------------------
mean = mean(E_CZE_B) t = .
Ho: mean = 0 degrees of freedom = 37
Ha: mean < 0 Ha: mean != 0 Ha: mean > 0
Pr(T < t) = . Pr(|T| > |t|) = . Pr(T > t) = .
I would like to know why all the p-values are missing here? Is it because E is a fixed value for all observations? If this is the case, how can I test this hypothesis, i.e. E=0?
Any help would be very much appreciated.
Anh
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