How is split-half reliability calculated and what are some best practices for doing so?

Question

What will be an ideal response?

Answer 1

An estimate of reliability may be derived from a single administration of a test by splitting the test statistically into two equivalent halves after it has been given, thus yielding two scores for each individual. This procedure is conceptually equivalent to the administration of alternate forms but on a single occasion. If the test is internally consistent, then any one item or set of items should be equivalent to any other item or set of items. Using split-half methods, error variance is attributed primarily to inconsistency in content sampling. In computing split-half reliability, the first challenge is how to split the test in order to obtain two halves that are equivalent in content, difficulty, means, and standard deviations. In most instances, it is possible to compute two separate scores for each individual based on his or her responses to odd items and even items. However, such estimates are not really estimates of internal consistency; rather, they yield spuriously high reliability estimates based on equivalence (Guion, 1965).
A preferable approach is to select the items randomly for the two halves. Random selection should balance out errors to provide equivalence for the two halves, as well as varying the number of consecutive items appearing in either half. A correlation coefficient computed on the basis of the two “half” tests will provide a reliability estimate of a test only half as long as the original. For example, if a test contains 60 items, a correlation would be computed between two sets of scores, each of which contains only 30 items. This coefficient underestimates the reliability of the 60-item test, since reliability tends to increase with test length. A longer test provides a larger sample of the content domain and tends to produce a wider range of scores, both of which have the effect of raising a reliability estimate.