We are receiving a lot of questions about relevant analyses in the Analyse-it Method Validation edition to help in evaluating new diagnostic tests in the fight against COVID-19. Below are some quick links that will help, but contact us if you have questions - we are working as normal.
Also see our latest blog post: Sensitivity/Specificity and The Importance of Predictive Values for a COVID-19 test
Exploratory factor analysis (EFA) identifies the underlying relationships between a large number of interrelated variables when there are no prior hypotheses about factors or patterns amongst the variables.
EFA is a technique based on the common factor model which describes the measured variables by a function of the common factors, unique factors, and error of measurements. Common factors are those that influence two or more measured variables, while unique factors influence only one measured variable.
The factor pattern matrix loadings are the linear combinations of the factors that make up the original standardized variables.
The factor structure matrix loadings are the correlation coefficients between the factors and the variables.
The factor correlation matrix coefficients are the correlation coefficients between the factors.