Missing values in two-level factorial designs
Missing data; Incomplete experiments; Factorial Fractional; Estimation methods.
Full and fractional factorial designs with 2 levels are widely used in various fields of knowledge, especially in industry. To analyze such experiments is necessary that all planned treatment combinations are performed and the answers are obtained. However, in practice, many experiments fail to be completed due to logistical problems, time or budget constraints. These experiments are called incomplete. In order to properly analyze such experiments, different methods are proposed in the literature. This study aims to present, compare and make critical reflections about methods for estimating missing data in factorial experiments with two levels.