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From |
John Antonakis <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Clustered Standard Errors vs HLM for Small Sample Project |

Date |
Mon, 18 Nov 2013 22:18:39 +0100 |

Thanks for the clarifications Austin.

I assumed that:

2. HLM = RE model.

Best, J. __________________________________________ John Antonakis Professor of Organizational Behavior Director, Ph.D. Program in Management 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 http://www.hec.unil.ch/people/jantonakis Associate Editor: The Leadership Quarterly Organizational Research Methods __________________________________________ On 18.11.2013 21:19, Austin Nichols wrote: > For good inference, you want not only many clusters, but also clusters > that are balanced (which means guidelines about 20 or 30 or 42 or 50 > clusters are less than helpful): > http://www.stata.com/meeting/13uk/nichols_crse.pdf > > When RE/HLM models and Cluster-Robust SE work well, they give similar > answers, but in some circumstances where they work poorly, they can > also give similar (wrong) answers: > https://appam.confex.com/appam/2013/webprogram/Paper6337.html > > You need to describe in more detail the source of correlations in > errors and regressors to get a good answer--on how to design a > simulation to indicate which approach is likely to give the best > inference in your setting. > > In his reply below, John Antonakis seems to be mixing up a comparison > between FE and RE (ssc describe xtoverid) with a comparison between FE > and pooled OLS with CRSE; whether or not you should use a fixed > effects method is a more complicated question than any one test will > answer, and depends very strongly on what you believe about > measurement error in your predictors. >

>> Hi: >>

>> use this program but Stata obviously). >>

>> be much more worried about omitted fixed-effects than just about robust >> standard errors--which are important too. See: >> >> Halaby, C. N. 2004. Panel models in sociological research: Theory into >> practice. Annual Review of Sociology, 30: 507-544. >> >> So, I would first check for omitted fixed-effects. If the Haumsan >> endogeneity test (can be tested with the user written command -xtoverid-

>> the Mundlak procedure: >> >> Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. 2010. On making >> causal claims: A review and recommendations. The Leadership Quarterly, >> 21(6): 1086-1120. >>

>> valid inference. >> >> Hth. >> J. >> >> __________________________________________ >> >> John Antonakis >> Professor of Organizational Behavior >> Director, Ph.D. Program in Management >> >> 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 >> http://www.hec.unil.ch/people/jantonakis >> >> Associate Editor: >> The Leadership Quarterly >> Organizational Research Methods >> __________________________________________ >> >> >> On 18.11.2013 03:06, [email protected] wrote: >>>

>>> different states. >>> >>> The minimum number of observations I have from a state is 3 and the >>> maximum number of observations I have is 108 with an average >>> of 23.3. I'm not interested in state level differences, I'm only

>>> fact that there may be some state level effects. >>>

>>> direction. The literature seems to say that HLM works best on larger

>>> my choice? Is there some other method I should use? >>> >>> Thank you in advance for your consideration. >>> >>> MK > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: Clustered Standard Errors vs HLM for Small Sample Project***From:*Austin Nichols <[email protected]>

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