According to Kline (2005), when conducting exploratory factor analysis (EFA) for new scale development, principal components analysis (PCA) provides a more realistic estimation of factor structure assuming that "the items are measured with errors."

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Exploratory Factor Analysis (EFA) is more appropriate for estimating factor structure when considering measurement errors, as it explicitly models errors, whereas Principal Components Analysis (PCA) does not.

According to Kline (2005), When Conducting Exploratory Factor Analysis (EFA)