Although there are many evaluated theories, only some of them are considered good theories based on certain evaluation criteria being met. To be considered a good theory, several evaluation criteria must be met, such as logical consistency, testability, and empirical validity. Logical consistency has two elements, scope and parsimony, both of which are interdependent. The scope of a theory refers to the range of explanations (Akers & Sellers, 2013, p. 5). If the scope of a theory is limited, then the theory itself is limited. For example, if a theory focuses only on one crime rather than multiple crimes, its scope may be limited. In addition to scope, parsimony refers to “using the fewest concepts and propositions possible to explain the widest range of phenomena” (Akers & Sellers, 2013, p. 5). Sparingly, it must be simple, but sufficient. An example of a theory with logical consistency is the theory of deterrence. Logical consistency is applicable to the theory because it recognizes that all crimes carry a threat/risk of punishment which leads to a deterrence from committing crimes. As a result, the theory is simple, but also covers a wide range of phenomena, like all crimes, that encompass both broad scope and parsimony. Besides logical consistency, testability is an important element when evaluating a theory. According to Akers & Sellers (2013), “a theory must be capable of being tested by objective and reproducible evidence” (p.5); thus, if the theory is not testable, it has no scientific value. There are several reasons why a theory may not be testable; such that its concepts may not be observable or reportable events and tautology. Tautology refers to a statement or assumption that is considered criminal (X) in the middle of paper (X), making it more likely to continue that lifestyle (Y). In addition to theories about causality, the quality of the empirical test is important. A theory that does not properly measure independent and dependent variables could result in insufficient methodological quality. Additionally, this could pose hypothesis problems. Furthermore, if the theory does not collect enough data from a connected, large, and diverse sample, then it is insufficient. All these elements are correlated to contribute to a sufficient empirical test. For example, if a theory suggests that all men who grow up in an abusive home will commit violent acts in the future, but does not collect data from a large enough population or does not include women in the study, then its empirical tests might be insignificant. which would lead to the theory not being empirically valid.