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The loading needed for statistical significance falls as sample size rises: about 0.40 at n = 200 but only 0.30 at n = 350, following Hair's guidelines. A loading of 0.62 therefore passes comfortably at n = 200 and explains 38.4% of the item's variance, since communality is the squared loading.
Significance thresholds
0.30 at n=350, 0.40 at n=200, 0.55 at n=100
Communality
variance explained = loading squared
Because significance testing compares the loading against its standard error, which shrinks as the square root of n.
Not necessarily. A 0.30 loading explains only 9% of variance, so practical significance usually demands 0.50 or more regardless of n.