Sensitivity Analysis in Principal Factor Analysis: A Numerical Investigation

Odaka, Yoshimasa; Tanaka, Yutaka

doi:10.2333/bhmk.17.27_87

Behaviormetrika

1990

DOI: 10.2333/bhmk.17.27_87

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Sensitivity Analysis in Principal Factor Analysis: A Numerical Investigation

Yoshimasa Odaka

Yutaka Tanaka

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1994

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Recent Advance in Sensitivity Analysis in Multivariate Statistical Methods

Tanaka

1994

Journal of the Japanese Society of Computational Statistics

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Methodologies have been developed in the last two decades for detecting influential observations and evaluating the stability of the results of analysis not only in regression and related methods but also in other multivariate methods. In developing these methodologies influence functions play important roles. The present paper shows that influence functions can be derived in various multivariate statistical methods and that a general strategy based on influence functions and its robust version are useful for detecting singly and/or jointly influential observations. Cases of principal component analysis, exploratory factor analysis and confirmatory factor analysis are studied with numerical examples.

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Recent Advance in Sensitivity Analysis in Multivariate Statistical Methods

Tanaka

1994

Journal of the Japanese Society of Computational Statistics

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Sensitivity Analysis in Principal Factor Analysis: A Numerical Investigation

Cited by 1 publication

References 15 publications

Recent Advance in Sensitivity Analysis in Multivariate Statistical Methods

Recent Advance in Sensitivity Analysis in Multivariate Statistical Methods

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