Although there are many studies devoted to person-fit statistics to detect inconsistent item score patterns, most studies are difficult to understand for nonspecialists. The aim of this tutorial is to explain the principles of these statistics for researchers and clinicians who are interested in applying these statistics. In particular, we first explain how invalid test scores can be detected using person-fit statistics; second, we provide the reader practical examples of existing studies that used person-fit statistics to detect and to interpret inconsistent item score patterns; and third, we discuss a new R-package that can be used to identify and interpret inconsistent score patterns.