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From |
John Antonakis <john.antonakis@unil.ch> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: re: tsset with non-integers |

Date |
Fri, 08 May 2009 07:30:08 +0200 |

OK Frank. Makes sense now.

Keep well, John. ____________________________________________________ Prof. John Antonakis Associate Dean Faculty of Business and Economics University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 Faculty page: http://www.hec.unil.ch/people/jantonakis&cl=en Personal page: http://www.hec.unil.ch/jantonakis ____________________________________________________ On 07.05.2009 23:07, Frank Gallo wrote:

<>Thank you all for your thoughts and comments, which have shed light oninaccurate suggestions from a book on statistics using SPSS.Best, Frank On May 7, 2009, at 1:32 PM, John Antonakis wrote:Oh....forgot to say; welcome to Stata. You won't regret it. SPSS hassome very serious limitations.Also, I just check and saw what SPSSs command does: it seems to checkfor serial correlation in adjacent observations. As Kit said, unlessthe data are specifically ordered for that purpose, checking forseriel correlation makes no sense.As for the clustering, I used the term in a generic sense to talk ofnested observations. If observations are not independent then you needto model this non-independence using the -cluster- option for the vce.Also, intercepts might vary between clusters. If so use -xttest0-after running -xtreg- to see if you need to model the random intercept.HTH, John. ____________________________________________________ Prof. John Antonakis Associate Dean Faculty of Business and Economics University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 Faculty page: http://www.hec.unil.ch/people/jantonakis&cl=en Personal page: http://www.hec.unil.ch/jantonakis ____________________________________________________ On 07.05.2009 19:02, Frank Gallo wrote:<>SPSS offers users the post regression estimation option to test theindependence of residuals terms using the Durbin-Watson test so thatusers can check the independence assumption. My data are not of thetime series type. As a stata beginner, I am trying to learn a stataequivalent approach. Thank you.Best, FrankOn Thursday, May 07, 2009, at 09:47AM, "Nick Cox"<n.j.cox@durham.ac.uk> wrote:Why can't you -tsset- the data?If your data are time series, you should know the times (dates).Specify the time variable to -tsset-.If they aren't, then serial correlation is presumably not defined orapplicable anyway.Nick n.j.cox@durham.ac.uk Frank Gallo Hi Eva,The way I understood Kit's response was that both suggestedapproaches (estat bgodfrey and wntestq) require the user to tssetthe data, which I cannot do. I am looking to test theautocorrelation of residuals terms so that I can check theregression assumption of indepence of errors. Thank you.On Thursday, May 07, 2009, at 09:31AM, "Eva Poen"<eva.poen@gmail.com> wrote:Frank, please tell us what you don't understand about the replies you have got so far. Kit gave recommendations for testing for autocorrelation in residuals. If it is serial correlation that you are after, you have time series (or panel) data, and should tell Stata about it, using the -tsset- command. See -help tsset-. If it is not serial correlation but some other kind of dependence, you need to be more specific about the type of data you have. Kit discouraged the use of -durbinh-, but if you insist on using it anyway, you need to -tsset- your data first. In any case, residuals are very unlikely to be integers. Your _time_ variable (e.g. years or quarters or months) could be integer. But that has nothing to do with your residuals. Eva 2009/5/7 Frank Gallo <fjgallo@mac.com>:<> Hi Nick & Kit,Thank you for your responses. My goal is only to check theindependence of residual terms following a regression run. Myreading of the durbinh command lead me to believe that it wouldhelp me achieve my goal. Can you suggest an alternative option tocheck the independence of residual terms that are non-integers?Thank you.Best, FrankOn Thursday, May 07, 2009, at 06:32AM, "Kit Baum" <baum@bc.edu>wrote:<> Frank saidWhat I would like to do, which I cannot find exactly in thearchives,is to check the independence of the residual terms (e) from a regression. I would like to run the -durbinh- command... Nick Cox answered the technical question re -tsset-. I do not recommend you rely on the -durbinh- command. It is a special case of the Breusch-Godfrey test in which you only consider AR(1) vs i.i.d. The -estat bgodfrey- postestimation command allows you to test forhigher-order autocorrelation as well (which might well be presentevenif an AR(1) coefficient is insignificant). Also consider using - wntestq-, which is an unconditional test of the residuals' autocorrelation function. (B-G is a conditional test in that it usesthe X matrix from the regression, whereas the Lung-Box-Pierce "Q"testmay be applied to any time series). All will require that thedata areproperly -tsset-.* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: re: tsset with non-integers***From:*Kit Baum <baum@bc.edu>

**Re: st: re: tsset with non-integers***From:*Frank Gallo <fjgallo@mac.com>

**Re: st: re: tsset with non-integers***From:*Eva Poen <eva.poen@gmail.com>

**Re: st: re: tsset with non-integers***From:*Frank Gallo <fjgallo@mac.com>

**RE: st: re: tsset with non-integers***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**RE: st: re: tsset with non-integers***From:*Frank Gallo <fjgallo@mac.com>

**Re: st: re: tsset with non-integers***From:*John Antonakis <john.antonakis@unil.ch>

**Re: st: re: tsset with non-integers***From:*Frank Gallo <fjgallo@mac.com>

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