According To Cohen And Swerdlik 2018, Reliability Means To B

According To Cohen And Swerdlik 2018 Reliability Means To Be Consis

According to Cohen and Swerdlik (2018), reliability in psychometric testing refers to the consistency of a measurement or assessment tool. The authors define a reliability coefficient as an index that indicates the ratio between the true score variance and the total observed variance in a test. This ratio provides a measure of the extent to which test scores are free from error and reflect the true ability or trait being measured. Three primary sources of error variance identified in testing include test construction, test administration, and test scoring and interpretation. These sources can introduce variability that affects the reliability of the test scores.

Measurement error is described by Cohen and Swerdlik as any disturbance associated with the measurement process that pertains to the measurement method rather than the trait being measured. This encompasses various factors that can influence the scores independently of the individual's true abilities or characteristics. Understanding these sources of error is essential to evaluating and improving the reliability of psychological assessments.

One common form of reliability assessment is internal consistency reliability, which measures the degree to which items within a test are correlated and collectively evaluate the same construct. In the example provided, an internal consistency reliability coefficient of .92 indicates high reliability, suggesting that the test items are strongly related and measure the same underlying trait. A high internal consistency coefficient means that the test is likely to produce consistent results across different administrations or similar groups.

Another important type of reliability is alternative forms reliability, which evaluates the consistency between different versions of the same test constructed to be parallel. Cohen and Swerdlik (2018) describe this as estimating the extent to which different test forms are affected by sampling error or other sources of measurement error. An example of this is administering two different versions of the same test to a person at different times. In the example, the alternate forms reliability coefficient is .82, indicating a high level of consistency between the two forms, thus supporting the test's reliability.

Test-retest reliability, on the other hand, assesses the stability of test scores over time by administering the same test to the same individuals at two different points. Cohen and Swerdlik (2018) note that the higher the correlation coefficient between the two test administrations, the more reliable the test is deemed to be. In the example, a test-retest coefficient of .50 is moderate but considered acceptable in some contexts, whereas a coefficient of .92 would signify excellent stability. It is important to recognize that the time interval between tests can influence reliability estimates; longer intervals tend to lower the coefficient due to potential intervening factors such as life events or traumatic experiences that can alter responses (Cohen & Swerdlik, 2018).

Moreover, Cohen and Swerdlik highlight that reliability estimates below .50 are generally viewed as unacceptable, indicating that the measurement may not be consistent enough to draw valid conclusions. They also emphasize the importance of considering possible intervening variables that may affect test scores between administrations, which can impact the reliability estimate.

In conclusion, reliability is an essential aspect of psychological measurement, reflecting the consistency and stability of test scores over time, across different forms, and within the items themselves. High reliability coefficients suggest that assessments provide dependable data, crucial for making accurate and valid inferences about individuals. Understanding the different types of reliability and the factors that influence them enables practitioners and researchers to select and develop more precise measurement tools, ultimately enhancing the validity and utility of psychological assessments (Cohen & Swerdlik, 2018).

References

• Cohen, R. J., & Swerdlik, M. (2018). Psychological Testing and Assessment. Capella.
• Guidelines for Psychological Testing and Assessment. American Psychological Association.
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• Autobiographical Memory and Cognitive Testing. Routledge.
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• Test Theory: A Unified Treatment. Psychology Press.
• Measurement in Education: A Guide to Test and Scoring. Routledge.
• Methods of Testing for Validity and Reliability. Routledge.