To measure internal consistency, psychologists must collect and analyze data with the same measure, and then use correlation tests to assess whether the items measure and reflect the same construct. A strong correlation indicates that the items accurately test for the same underlying “construct”, like intelligence, self-esteem, anxiety, or depression. In a test with high internal consistency, different peoples’ scores on various items should correlate with each other. Within a single test, internal consistency measures the consistency of individuals’ responses across questions, or “items”. This assessment requires advanced statistical skills: one of the many reasons why psychologists need higher education to perform research.
To assess test-retest reliability, psychologists must use the measure at least twice with the same group of people, and then analyze the test-retest correlation between the different sets of scores. Using this example, a psychological measure with high test-retest reliability should produce about the same scores for the same individual over time. For example, a person who is highly intelligent is expected to have the same or similar cognitive abilities next week, next year, and even in several years. Test-retest reliability measures the extent to which results are consistent across time.
When discussing the validity of a measure, psychologists typically refer to three types of reliability. Psychologists may use a variety of tests to assess a group or individual, depending on a client’s needs or a specific research question. A clinical interview, when a psychologist speaks to a patient about their concerns and history.Some examples of psychological measures include: These psychological tests contain a set of stimuli (usually a series of questions or tasks), which are given to participants and used to assess a “sample” of their behavior under a standard condition. Therapists Can Offer Knowledge And SupportĪccording to the American Psychological Association (APA), reliability is the trustworthiness or consistency of a measure or test used for research.
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