When carrying out factor analysis (Exploratory factor analysis) using SPSS, I found that people supress the value under certain values in factor loading and only take values above certain point are considered as significant loading.

Many suggest this value to be 0.30 (and load only value above 0.30 as significant factor)

Whereas some other consider 0.50 as value for significant loading.

I found the if value is high, then only high loading factors are in each factor which looks good but it tends to ignore the high loading cross loading. For example, if any item is cross loading in 2 factors may be with 0.60 in one and 0.48 in another, that 0.48 will be supressed or ignored or cross loading won’t be visible.

If we take 0.30 as boundary to decide significant loading, then even low value (i.e 0.31 or 0.35) may be loaded in each factor and there may be many cross loading.

So, I am bit confused. High value is good to take significant loading or low value?

0.50 is better or 0.30

In my case, the factors are loading same for both values which left me wondering which value should I take?