Tag: Statistical modeling

According to a 2025 review on landscape genomics, redundancy analysis (RDA) is a highly versatile tool for identifying and evaluating relationships between genetic and environmental variation. A comprehensive guide on what is the RDA analysis is essential for researchers looking to understand and apply this multivariate statistical method effectively.

Statistically, factor analysis is a powerful technique for modeling the variance among observed variables as a function of unobserved, or latent, entities. How is EFA different from CFA? At its core, EFA is an exploratory method for uncovering potential structures, while CFA is a confirmatory method for testing a predefined structure.

In statistics, a perfect model with zero error is virtually impossible. This is why residual checks are a critical diagnostic tool, quantifying the difference between observed data and the model's predictions to help evaluate model performance and adherence to assumptions.