What Is Reliability?


Reliability refers to consistency — if you measure something and get the same results each time, then it’s reliable. This is similar to a scale that measures weight consistently or a tape measure that measures inches consistently.

There are two types of reliability: test-retest and internal consistency. Test-retest reliability is assessed by administering a measure to a group of people, using it again on the same group at a later time, and comparing the two sets of scores. You then calculate the correlation between the two sets of scores and compute Pearson’s r. The higher the r, the more likely that the test will provide reliable results over time. Take a look at techmanufacture.com to understand more regarding it.

Test-retest reliability is a good indicator of test validity, and you can use it to help select tests for your research or evaluations. The reliability coefficient of a test is often reported in the test manual and can give you an idea of how reliable it is. It is important to remember that the size of the reliability coefficient doesn’t indicate perfect reliability.

Internal consistency (also called split-half reliability) is the extent to which items in a test measure the same thing, or the same construct. This is usually determined by analyzing the average inter-item correlation or by splitting the items in the test into two sets and calculating the correlation between them.

This is a good indicator of test validity and can be used to determine whether or not a measure is valid, for example, if it accurately reflects the way introverts think. It also helps prevent personal bias in the interpretation of results by examining the way different factors influence the outcome.

Reliability can also be measured when you administer a measure to a group of people and repeat it to the same group of people at a later time, again using the same set of questions. A high test-retest reliability indicates that the measure is repeatable and reliable over time.

Parallel forms reliability assesses how consistent test results are when you administer two different versions of a measure that each contain items that probe the same construct, skill or knowledge base to the same group of individuals. This is a good indicator of test validity, but you must ensure that all of the questions or measures used in each version reflect the same theory and are carefully formulated to measure the same thing.

The most common way to measure parallel forms reliability is to produce a large set of questions that all pertain to the same construct, and then divide them into two sets, which are then administered to the same group of respondents. Then, you calculate the correlation between the two sets of scores to determine their parallel form reliability.

This is a good indicator of test validity, although it can be more difficult to measure than either test-retest or internal consistency reliability. It is also more expensive and requires repeated tests to obtain adequate data, but it can be helpful in avoiding the need for re-testing after an experiment is completed.

Zupyak is the world’s largest content marketing community, with over 300 000 members and 3 million articles. Explore and get your content discovered.