2021
DOI: 10.1016/j.sapharm.2020.07.027
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Issues and recommendations for exploratory factor analysis and principal component analysis

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Cited by 215 publications
(134 citation statements)
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“…Compared with the prevalent variance-based algorithms, PLS methods provide a higher statistical power, and they have "almost no limiting assumptions regarding the model specifications and data'' (Hair et al, 2011) such as sample size or distribution of data (Hair et al, 2017). Although there are several "golden rules'' about the sample size required for covariance-based factor analysis methods (Schreiber, 2021), PLS based analysis "can be a very sensible methodological choice if sample size is restricted" (Reinartz et al, 2009). The data collected from evaluators of mobile apps are used for comparison with data collected on website users through student t-tests, to explore the applicability of SUPR-Q for assessing user experience in mobile apps.…”
Section: Discussionmentioning
confidence: 99%
“…Compared with the prevalent variance-based algorithms, PLS methods provide a higher statistical power, and they have "almost no limiting assumptions regarding the model specifications and data'' (Hair et al, 2011) such as sample size or distribution of data (Hair et al, 2017). Although there are several "golden rules'' about the sample size required for covariance-based factor analysis methods (Schreiber, 2021), PLS based analysis "can be a very sensible methodological choice if sample size is restricted" (Reinartz et al, 2009). The data collected from evaluators of mobile apps are used for comparison with data collected on website users through student t-tests, to explore the applicability of SUPR-Q for assessing user experience in mobile apps.…”
Section: Discussionmentioning
confidence: 99%
“…Correlation matrix items were all above 0.40 indicating a strong relationship between items and construct. [15] The KMO test result was 0.92 and 0.89 for maintenance and complication, respectively. This value is considered indicative of sampling adequacy and that factor analysis would yield reliable and distinct factors.…”
Section: Data Measurementmentioning
confidence: 94%
“…In line with relevant psychometric protocol (Schreiber, 2021), before testing the hypothesized relationships between the factors related to commitment, it was particularly necessary to test the empirical distinctiveness of the sub-constructs of commitment. Thus, an exploratory factor analysis was conducted to determine the underlying factor structure of commitment and arrive at a decision whether to retain the original factor structure.…”
Section: Methodsmentioning
confidence: 99%