Impact of Conditions which Affect Exploratory Factor Analysis

Some things cannot be observed directly and must be inferred from multiple indirect measurements, for example human experiences accessed through a variety of survey questions. Exploratory Factor Analysis (EFA) provides a data-driven method to optimally combine these indirect measurements to infer some number of unobserved factors. Ideally, EFA should identify how many unobserved factors the indirect measures help estimate (factor extraction), as well as accurately capture how well each indirect measure estimates each factor (parameter recovery).