A Monte Carlo Comparison of Relative Importance Methodologies  

Oleh:

Ployhart, Robert E. ; LeBreton, James M. ; Ladd, Robert T.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Organizational Research Methods vol. 7 no. 3 (Jul. 2004), page 258-282.
Topik: Monte Carlo Method; relative importance; monte carlo simulation; dominance analysis
Fulltext: 258.pdf (185.89KB)

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Perpustakaan Pusat (Semanggi) Nomor Panggil: OO3.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This article reports the results of a monte carlo simulation comparing four different indices of relative importance (squared correlation, squared beta, product measure, epsilon) to a relatively new method called dominance analysis. Conceptually and empirically, dominance analysis represents an improvement over traditional indices of relative importance. Eight experimental dactors were manipulated in the simulations : mean and standard deviation of validity for each predictor, mean and standard deviation of collinearity for two sets of predictors, number of predictors, and presence of simple structure. Of these factors, the number of predictors and the mean collinearity were most strongly related to discrepancies among the rank orders computed using the different importance methods. Across all experimental conditions, the epsilon statistic demonstrated the greatest convergence and beta weights and correlation coefficients the greatest divergence with dominance.

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