Multivariate meta analysis with potentially correlated marketing study results

Research output: Contribution to journalArticle

18 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)500-510
Number of pages11
JournalNaval Research Logistics
Volume47
Issue number6
DOIs
Publication statusPublished - 2000 Sep 1

Fingerprint

Marketing
Random errors
Type II error
Specifications
Variance Components
Model Specification
Random Error
Meta-analysis
Military
Univariate
Monte Carlo Simulation
Model
Evaluate
Simulation

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Ocean Engineering
  • Management Science and Operations Research

Cite this

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Multivariate meta analysis with potentially correlated marketing study results. / Sohn, So Young.

In: Naval Research Logistics, Vol. 47, No. 6, 01.09.2000, p. 500-510.

Research output: Contribution to journalArticle

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