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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 16:26:01 +0100 |

Hi:

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:

I'm using STATA 10 and I'm trying to figure out whether to use clustered standard errors or HLM.I have 233 observations from agencies located in 10 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 interested in results from the agency level and I want to account for the fact that there may be some state level effects. The literature I've read so far doesn't seem to point me in any definite direction. The literature seems to say that HLM works best on larger datasets, but it also seems to say that you need at least 20 clusters for either method to be effective. Does anyone have a suggestion for which of these two methods I should use, or at least what I should consider in making 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/

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