引述 :『No. Results of factor analysis are not affected by standardization, which is built into the procedure. Note, however, that standardization (subtracting the mean, dividing by the standard deviation) scales data in a sample-specific way. If the research purpose is to compare factor structures between two or more samples, then one should use the covariance matrix rather than the correlation matrix as input to factor analysis (Kim and Mueller, 1978b: 76). However, the covariance method has problems when the variables are measured on widely different scales (ex., income measure to $100,000 and education measured to 22 years). Kim and Mueller recommend multisample standardization for this case (subtracting the grand mean of all samples, and dividing by the standard deviation of all cases) prior to computing the sample covariance matrix (p. 76). However, in practice factor comparison between samples usually is based on ordinary factor analysis of correlation matrices. Reference Kim, Jae-On and Charles W. Mueller (1978a). Introduction to factor analysis: What it is and how to do it. Thousand Oaks, CA: Sage Publications, Quantitative Applications in the Social Sciences Series, No. 13. Kim, Jae-On and Charles W. Mueller (1978b). Factor Analysis: Statistical methods and practical issues. Thousand Oaks, CA: Sage Publications, Quantitative Applications in the Social Sciences Series, No. 14. 』