A statistical approach to Saaty's scaling method for priorities

Piet de Jong

doi:10.1016/0022-2496(84)90013-0

A statistical approach to Saaty's scaling method for priorities

Piet de Jong^*

^*Corresponding author for this work

Research output: Contribution to journal › Article

99 Citations (Scopus)

Abstract

This paper investigates the logarithmic least squares (LLSM) approach to Saaty's (Journal of Mathematical Psychology, 1977, 5, 234-281) scaling method for priorities in hierarchical structures. It is argued that statistical criteria are important in deciding the scaling method controversy. It is shown that LLSM is statistically optimal under a number of realistic and practical models. Variances and covariances of parameter estimates are derived. The covariance matrix associated with overall priority differences is also developed. These results allow for a significance analysis of apparent priority differences.

Original language	English
Pages (from-to)	467-478
Number of pages	12
Journal	Journal of Mathematical Psychology
Volume	28
Issue number	4
DOIs	https://doi.org/10.1016/0022-2496(84)90013-0
Publication status	Published - 1984
Externally published	Yes

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title = "A statistical approach to Saaty's scaling method for priorities",

abstract = "This paper investigates the logarithmic least squares (LLSM) approach to Saaty's (Journal of Mathematical Psychology, 1977, 5, 234-281) scaling method for priorities in hierarchical structures. It is argued that statistical criteria are important in deciding the scaling method controversy. It is shown that LLSM is statistically optimal under a number of realistic and practical models. Variances and covariances of parameter estimates are derived. The covariance matrix associated with overall priority differences is also developed. These results allow for a significance analysis of apparent priority differences.",

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AB - This paper investigates the logarithmic least squares (LLSM) approach to Saaty's (Journal of Mathematical Psychology, 1977, 5, 234-281) scaling method for priorities in hierarchical structures. It is argued that statistical criteria are important in deciding the scaling method controversy. It is shown that LLSM is statistically optimal under a number of realistic and practical models. Variances and covariances of parameter estimates are derived. The covariance matrix associated with overall priority differences is also developed. These results allow for a significance analysis of apparent priority differences.

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