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Title: Principal Component Analysis vs. Exploratory Factor Analysis
Resulting in 1 citation.
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Suhr, Diana D. |
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Principal Component Analysis vs. Exploratory Factor Analysis Presented: Philadelphia, PA, Paper 203-30, SAS® Users Group International Conference (SUGI 30), Proceedings of the Thirtieth Annual, April 10-13, 2005. Also: http://www2.sas.com/proceedings/sugi30/203-30.pdf#search=%22how%20to%20compute%20the%20PIAT%20math%20score%22 Cohort(s): Children of the NLSY79 Publisher: SAS Institute Inc. Keyword(s): Behavior; Data Analysis; Economics of Minorities; Ethnic Differences; Home Environment; Labor Market Outcomes; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Psychological Effects; Racial Differences; Statistical Analysis Permission to reprint the abstract has not been received from the publisher. Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) are both variable reduction techniques and sometimes mistaken as the same statistical method. However, there are distinct differences between PCA and EFA. Similarities and differences between PCA and EFA will be examined. Examples of PCA and EFA with PRINCOMP and FACTOR will be illustrated and discussed. Copyright © 2005 by SAS Institute Inc., Cary, NC, USA. |
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Bibliography Citation
Suhr, Diana D. "Principal Component Analysis vs. Exploratory Factor Analysis." Presented: Philadelphia, PA, Paper 203-30, SAS® Users Group International Conference (SUGI 30), Proceedings of the Thirtieth Annual, April 10-13, 2005. |