wald Chi-Squared stat and F stat
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iloverats
- Posts: 39
- Joined: Thu Dec 02, 2010 10:32 am
wald Chi-Squared stat and F stat
dear
when i do the wald test using "test" "restrict" or "exclude"
why can not i get the wald Chi-Squared stat, but F stat
how can i get the wald Chi-Squared stat?
when i do the wald test using "test" "restrict" or "exclude"
why can not i get the wald Chi-Squared stat, but F stat
how can i get the wald Chi-Squared stat?
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moderator
- Site Admin
- Posts: 269
- Joined: Thu Oct 19, 2006 4:33 pm
Re: wald Chi-Squared stat and F stat
See Section 6.2 of the User's Guide. In particular, see "Applicability of the Testing Instructions" (page 222 of the Version 7 edition).
Regards,
Tom Maycock
Regards,
Tom Maycock
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iloverats
- Posts: 39
- Joined: Thu Dec 02, 2010 10:32 am
Re: wald Chi-Squared stat and F stat
thank you Tommoderator wrote:See Section 6.2 of the User's Guide. In particular, see "Applicability of the Testing Instructions" (page 222 of the Version 7 edition).
Regards,
Tom Maycock
just use "robust" option ?
this Chi-Squared stat is Heteroscedasticity adjustment
how can i get the Chi-Squared stat which is not Heteroscedasticity adjustment?
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TomDoan
- Posts: 7825
- Joined: Wed Nov 01, 2006 4:36 pm
Re: wald Chi-Squared stat and F stat
The ROBUST option will give you a completely different covariance matrix. If what you want is a conventional Wald test in chi-squared form for a linear regression, you would need to multiply byiloverats wrote:thank you Tommoderator wrote:See Section 6.2 of the User's Guide. In particular, see "Applicability of the Testing Instructions" (page 222 of the Version 7 edition).
Regards,
Tom Maycock
just use "robust" option ?
# of restrictions x degrees of freedom / observations
The last two factors corrects for the F-statistic using the degrees of freedom adjusted estimate for the variance (rather than the maximum likelihood one) and first corrects for the F using the difference scaled by the number of restrictions. However, I would generally not recommend using the Wald form when an F is sensible (even when the F doesn't have a finite sample justification). The F form is more conservative and more likely to give something closer to the proper behavior.