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From |
"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: The correct order for testing for different kinds of endogeneity |

Date |
Thu, 26 Mar 2009 10:58:54 -0700 |

I've been reading the book by Gelman and Hill (Cambridge) "Data analysis Using Regression and Multilevel/Hierarchical Models" which gives a beautiful listing of potential assumption violations - First is model validity, last is normality (total 7). It's focused on R and WinBugs, but Stata does get a mention or two. I recommend it highly. Tony Peter A. Lachenbruch Department of Public Health Oregon State University Corvallis, OR 97330 Phone: 541-737-3832 FAX: 541-737-4001 -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten buis Sent: Thursday, March 26, 2009 8:34 AM To: statalist@hsphsun2.harvard.edu Subject: Re: st: The correct order for testing for different kinds of endogeneity --- On Thu, 26/3/09, Stephen Armah wrote: > should I first test for auto-correlation and > heteroskedasticity in Stata before testing for > endogeneity or is is better to do the reverse? Any such sequence you shoose will strictly speaking be wrong, unless you can frame the sequence of tests in way that is similar to (Marcus, Peritz, Gabriel 1976). I wouldn't worry too much about that though. The biger problem is that testing of model assumptions is a pretty horrible idea anyhow. The very purpose of a model is to simplify reality, ergo the assumptions are supposed to be wrong, otherwise the model would be a lousy simplification. However, we don't want the assumptions to be too wrong, otherwise the results would not say much either. Statistical testing is not designed for this kind of tradeoff: The logic behind testing is that a hypothisis is either true or false, while when we do model selection we already know that the assumption is false but we want to see whether an assumption is either useful or not useful. For this reason graphical investigations of the various model assumptions are by far preferable I know that this is a rant and that opions differ on this. If a reviewer/editor/supervisor/peer asks you for such a test, than you should just give it to them. Just don't take those tests too serious, and don't forget to look at the graphs. -- Maarten Marcus, R, E. Perity, and K.R. Gabriel. 1976. On closed testing procedures with special reference to ordered analysis of variance. Biometrika 63:655--660. ----------------------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://home.fsw.vu.nl/m.buis/ ----------------------------------------- * * 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: The correct order for testing for different kinds of endogeneity***From:*Stephen Armah <armah.stephen@gmail.com>

**Re: st: The correct order for testing for different kinds of endogeneity***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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