Varimax rotation based on gradient projection needs between 10 and more than 500 random start loading matrices for optimal performance

TL;DR

This study evaluates the performance of gradient projection rotation (GPR) with Varimax criterion in PCA, revealing that using multiple random start matrices improves results, with specific recommendations for different component and sample sizes.

Contribution

It provides empirical guidelines on the number of random start matrices needed for optimal GPR-Varimax rotation performance in PCA.

Findings

GPR-Varimax performs better with at least 10 random start matrices.

Performance improves with larger sample sizes and Kaiser-normalization.

Recommendations vary based on number of components and sample size.

Abstract

Gradient projection rotation (GPR) is a promising method to rotate factor or component loadings by different criteria. Since the conditions for optimal performance of GPR-Varimax are widely unknown, this simulation study investigates GPR towards the Varimax criterion in principal component analysis. The conditions of the simulation study comprise two sample sizes (n = 100, n = 300), with orthogonal simple structure population models based on four numbers of components (3, 6, 9, 12), with- and without Kaiser-normalization, and six numbers of random start loading matrices for GPR-Varimax rotation (1, 10, 50, 100, 500, 1,000). GPR-Varimax rotation always performed better when at least 10 random matrices were used for start loadings instead of the identity matrix. GPR-Varimax worked better for a small number of components, larger (n = 300) as compared to smaller (n = 100) samples, and when loadings were Kaiser-normalized before rotation. To ensure optimal (stationary) performance of GPR-Varimax in recovering orthogonal simple structure, we recommend using at least 10 iterations of start loading matrices for the rotation of up to three components and 50 iterations for up to six components. For up to nine components, rotation should be based on a sample size of at least 300 cases, Kaiser-normalization, and more than 50 different start loading matrices. For more than nine components, GPR-Varimax rotation should be based on at least 300 cases, Kaiser-normalization, and at least 500 different start loading matrices.