The Reliability of Linearly Equated Tests
Copyright policy )The Reliability of Linearly Equated Tests
An asymptotic expression for the reliability of a linearly equated test is developed using normal theory. The reliability is expressed as the product of two terms, the reliability of the test before equating, and an adjustment term. This adjustment term is a function of the sample sizes used to estimate the linear equating transformation. The results of a simulation study indicate close agreement between the theoretical and simulated reliability values for samples greater than 200. Findings demonstrate that samples as small as 300 can be used in linear equating without an appreciable decrease in reliability.
reliability, linear equating transformation, adjustment term, simulation, random effects model, linearly equated test, classical test theory, sample sizes, asymptotic standard errors, measurement error, Applications of statistics to psychology
reliability, linear equating transformation, adjustment term, simulation, random effects model, linearly equated test, classical test theory, sample sizes, asymptotic standard errors, measurement error, Applications of statistics to psychology
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