Deutsch: Empirisches Kriterium-Keying / Español: Clave de criterio empírico / Português: Chave de critério empírico / Français: Clé de critère empirique / Italiano: Chiave di criterio empirico /
Empirical criterion keying refers to an approach to test Development that emphasizes the selection of items that discriminate between normal individuals and members of different diagnostic groups, regardless of whether the items appear theoretically relevant to the diagnoses of interest.
Empirical criterion keying is a method used in psychological assessment to develop scales and measure personality traits or psychological constructs. The approach involves identifying items that discriminate well between individuals who score high and low on a particular criterion, such as a symptom or behavior, and then using those items to create a scale.
Empirical criterion keying is used to develop measures in a wide range of domains, including clinical psychology, personality psychology, and industrial-organizational psychology. For example, researchers may use this method to develop a measure of depression by selecting items that differentiate between individuals who meet diagnostic criteria for depression and those who do not.
One example of the use of empirical criterion keying is the development of the Minnesota Multiphasic Personality Inventory (MMPI), a widely used psychological assessment tool. The MMPI was developed using an empirical criterion keying approach to identify items that discriminated between psychiatric patients and non-patients.
Another example is the development of the Sixteen Personality Factor Questionnaire (16PF), which measures 16 primary personality traits. The 16PF was developed using empirical criterion keying to identify items that differentiated between individuals with high and low scores on each of the 16 traits.
Empirical criterion keying can be a useful approach for developing measures of psychological constructs, as it allows researchers to identify items that are most relevant for measuring the construct of interest. However, it is important to note that this method is not without limitations and potential biases, such as sampling bias and response biases, and researchers must take steps to ensure the validity and reliability of the measures developed using this approach.