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Multivariate meta analysis with potentially correlated marketing study results

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  • So Young Sohn

Abstract

A univariate meta analysis is often used to summarize various study results on the same research hypothesis concerning an effect of interest. When several marketing studies produce sets of more than one effect, multivariate meta analysis can be conducted. Problems one might have with such a multivariate meta analysis are: (1) Several effects estimated in one model could be correlated to each other but their correlation is seldom published and (2) an estimated effect in one model could be correlated to the corresponding effect in the other model due to similar model specification or the data set partly shared, but their correlation is not known. Situations like (2) happen often in military recruiting studies. We employ a Monte‐Carlo simulation to evaluate how neglecting such potential correlation affects the result of a multivariate meta analysis in terms of Type I, Type II errors, and MSE. Simulation results indicate that such effect is not significant. What matters is rather the size of the variance component due to random error in multivariate effects. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 500–510, 2000.

Suggested Citation

  • So Young Sohn, 2000. "Multivariate meta analysis with potentially correlated marketing study results," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(6), pages 500-510, September.
    • Handle: RePEc:wly:navres:v:47:y:2000:i:6:p:500-510
    DOI: 10.1002/1520-6750(200009)47:63.0.CO;2-Z
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    1. Sohn, S. Y., 1996. "Random effects meta analysis of military recruiting," Omega, Elsevier, vol. 24(2), pages 141-151, April.
    2. John T. Warner, 1990. "MILITARY RECRUITING PROGRAMS DURING THE 1980s: THEIR SUCCESS AND POLICY ISSUES," Contemporary Economic Policy, Western Economic Association International, vol. 8(4), pages 47-67, October.
    3. Cyril E. Kearl & David K. Horne & Curtis L. Gilroy, 1990. "Army Recruiting In A Changing Environment," Contemporary Economic Policy, Western Economic Association International, vol. 8(4), pages 68-78, October.
    4. Fern, Edward F & Monroe, Kent B, 1996. "Effect-Size Estimates: Issues and Problems in Interpretation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 23(2), pages 89-105, September.
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