The internal validity of a measurement instrument is an essential criterion to ensure that the independent variable influences only the observed variations in the dependent variable. According to the work of Jean-Claude Andréani and Françoise Conchon, it is crucial to formulate hypotheses before the study and to verify them using analyses such as correlation, regression, factor analysis, or typology. Validating these hypotheses against theoretical data makes them provisionally accepted; this is called corroboration. However, in qualitative research, the lack of statistical tests poses a challenge, hence the importance of interpretative validity. In contrast, in quantitative studies, confirming internal validity generally does not present major difficulties. According to Jean-Louis Chandon and Florence Dano, to test a theoretical structure, it is possible to compare this structure to the matrix of distances between objects without necessarily resorting to constructing empirical partitions, simply by using validity indices.