A longitudinal study, such as a cohort or clinical trial, has the virtue of following the logical sequence in which occurs the components of causality phenomenon. However, in a cross-sectional survey, this logical sequence does not exist, because the three components are measured at one time: the basal state, maneuver, and result. However, the design of "clinical judgment" helps us to rebuild these components artificially in the time sequence in which they occurred. The way the population is assembled and how information is obtained, transversally and retrospectively, carries the risk of bias. While trying to associate a probable maneuver to an outcome in a pathological situation is difficult and often causes bias, a cross-sectional survey is the best to show the development of healthy people simulating a longitudinal study, like the height and weight estimation according to age. This type of design has been called "a longitudinal cross sectional study."