Browsing by Author "Woodruff, David J."

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    A comparison of three linear equating methods for the common-item nonequivalent-populations design
    (1989) Woodruff, David J.
    Three linear equating methods for the common-item nonequivalent-populations design are compared using an analytical method. The analysis investigated the behavior of the three methods when the true-score correlation between the test and anchor was less than unity, a situation that may occur in practice. The analysis is graphically illustrated using data from a test equating situation. Conclusions derived from the analysis have implications for the practical application of these equating methods. Index terms: congeneric model, Levine equating method, linear equating, Tucker equating method.
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    Estimating measures of pass-fail reliability from parallel half-tests
    (1989) Woodruff, David J.; Sawyer, Richard L.
    Two methods are derived for estimating measures of pass-fail reliability. The methods require only a single test administration and are computationally simple. Both are based on the Spearman-Brown formula for estimating stepped-up reliability. The non-distributional method requires only that the test be divisible into parallel half-tests; the normal method makes the additional assumption of normally distributed test scores. Bias for the two procedures is investigated by simulation. For nearly normal test score distributions, the normal method performed slightly better than the non-distributional method, but for moderately to severely skewed or symmetric platykurtic test score distributions the non-distributional method was superior. Test results from a licensure examination are used to illustrate the methods. Index terms: Cohen’s kappa, licensure examinations, pass-fail reliability, reliability, Spearman-Brown formula.
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    Statistical inference for coefficient alpha
    (1987) Feldt, Leonard S.; Woodruff, David J.; Salih, Fathi A.
    Rigorous comparison of the reliability coefficients of several tests or measurement procedures requires a sampling theory for the coefficients. This paper summarizes the important aspects of the sampling theory for Cronbach’s (1951) coefficient alpha, a widely used internal consistency coefficient. This theory enables researchers to test a specific numerical hypothesis about the population alpha and to obtain confidence intervals for the population coefficient. It also permits researchers to test the hypothesis of equality among several coefficients, either under the condition of independent samples or when the same sample has been used for all measurements. The procedures are illustrated numerically, and the assumptions and derivations underlying the theory are discussed.