Promax is:

Promax is:

• A. A data transformation used to standardize variables.
• B. A method of oblique rotation that is computationally faster than direct oblimin and so useful for large data sets.
• C. An orthogonal rotation method with strict independence.
• D. A nonparametric test for distributions.

Answer: (B)

Promax is an oblique rotation used in factor analysis, which means it allows the factors to be correlated rather than forcing them to be independent. The typical approach is to start with a factor solution similar to varimax and then transform the loading pattern by raising loadings to a power to create a simpler structure, followed by rotating to an oblique solution. This method is designed to be computationally efficient, using an approximate route rather than the more intensive exact optimization that direct oblimin requires, making it faster for large data sets. It’s not about standardizing variables, it’s not an orthogonal rotation (which would enforce independence among factors), and it’s not a nonparametric test for distributions.

Promax is an oblique rotation used in factor analysis, which means it allows the factors to be correlated rather than forcing them to be independent. The typical approach is to start with a factor solution similar to varimax and then transform the loading pattern by raising loadings to a power to create a simpler structure, followed by rotating to an oblique solution. This method is designed to be computationally efficient, using an approximate route rather than the more intensive exact optimization that direct oblimin requires, making it faster for large data sets. It’s not about standardizing variables, it’s not an orthogonal rotation (which would enforce independence among factors), and it’s not a nonparametric test for distributions.