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From |
Nicholas Miceli <nsmiceli@yahoo.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Org. level vs. individual level data analyses. |

Date |
Fri, 6 Sep 2002 11:20:04 -0700 (PDT) |

Imagine the following study of relationships between pay and performance. In a given industry, at the organizational level, firms' data exists as follows: functional area --------------- firm payroll a b c ---- ------- - - - 1 1500 1 2 3 2 3000 3 4 5 3 1750 5 3 1 . . . n Areas "a," "b," and "c" have several variables used to assess performance within these areas. At the individual level, persons could have data in one, two, or possibly all three categories. No individual will have no data in all categories, but most individuals will have date in one of three, or two of three categories. At the organizational level, all organizations will have data in all categories. Most of the organizational level studies on this industry have used multiple regression as main effects models only. Accordingly, I have seen few, if any, studies in this area looking at the potential interaction between these functional areas. At the individual level, most studies have been conducted within functional area, once again, with main effects multiple regression. Some of the studies have gone so far as to argue that prediction at the individual level is done better by using organizational level results, and applying them to individual level cases. My questions are: 1. Is it not fundamentally problematic to make inferences or predictions about individuals from organizational level data (i.e., ecological fallacy)? 2. Would the organizational level beta weights be somewhat misstated for individuals because they do not take into account the distribution, incidence and prevalence of the attributes at the individual level? 3. Because individual level studies have been done within functional area, would relative worth (equity) analyses be more accurate if the variables were aggregated at the individual level (with zeroes indicating absence of a trait), and a regression equation then estimated? I would think that the resulting beta weights would be more accurately estimated for individuals, than using the organizational level equations. 4. Previous studies have not used factor analytic methods (for data reduction; surrogate variable selection; or factor score construction), nor have they used interaction terms in the analyses. Would factor analysis more accurately reflect the underlying construct structures and interrelationships between the variables at the individual level, or the organizational level? I would like to be able to examine whether there is interaction between the constructs. I believe that factor analysis for data reduction would be a valuable approach. If you have suggestions, please email me directly. Responses can and will be shared with the list, after receipt of suggestions seems to be complete (unless, of course, you want your comments kept private). Regards, Nick Miceli __________________________________________________ Do You Yahoo!? Yahoo! Finance - Get real-time stock quotes http://finance.yahoo.com * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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