Construct valdity relates to whether a particular psychometric assessment...
Lead consultant at Test Partnership, Ben Schwencke, explains what is factor analysis.
Factor analysis is a statistical method used to identify underlying patterns or factors in a set of variables. It is often used in psychometrics and social sciences to identify the underlying structure of a test or measure. Factor analysis is used to reduce a large number of variables into a smaller number of factors that explain the greatest amount of variance in the data. The goal of factor analysis is to identify the underlying dimensions that account for the relationships among the variables.
Factor analysis is based on the idea that a set of observed variables are correlated with each other because they measure the same underlying construct or factor. For example, a test of intelligence may include questions measuring verbal ability, mathematical ability, and spatial ability. Factor analysis can be used to identify if these variables are measuring the same underlying construct of intelligence.
There are different types of factor analysis, such as principal component analysis and exploratory factor analysis. These methods differ in how they extract the factors and the assumptions they make about the data.
Factor analysis is an important tool in psychometrics as it allows researchers to identify the underlying dimensions that account for the relationships among the variables and reduce the number of variables. It helps to identify the structure of a test or measure, which improves the reliability and validity of the test. It also helps to identify items that might not be measuring the construct of interest, which can be removed from the test.