Browsing by Author "Skaggs, Gary"

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    A comparison of pseudo-Bayesian and joint maximum likelihood procedures for estimating item parameters in the three-parameter IRT model
    (1989) Skaggs, Gary; Stevenson, José
    This study compared pseudo-Bayesian and joint maximum likelihood procedures for estimating item parameters for the three-parameter logistic model in item response theory. Two programs, ASCAL and LOGIST, which employ the two methods were compared using data simulated from a three-parameter model. Item responses were generated for sample sizes of 2,000 and 500, test lengths of 35 and 15, and examinees of high, medium, and low ability. The results showed that the item characteristic curves estimated by the two methods were more similar to each other than to the generated item characteristic curves. Pseudo-Bayesian estimation consistently produced more accurate item parameter estimates for the smaller sample size, whereas joint maximum likelihood was more accurate as test length was reduced. Index terms: ASCAL, item response theory, joint maximum likelihood estimation, LOGIST, parameter estimation, pseudo-Bayesian estimation, three-parameter model.
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    Effect of examinee ability on test equating invariance
    (1988) Skaggs, Gary; Lissitz, Robert W.
    Previous research on the application of IRT methodology to vertical test equating has demonstrated conflicting results about the degree of invariance shown by these methods with respect to examinee ability. The purpose of this study was to examine IRT equating invariance by simulating the vertical equating of two tests under varying conditions. Rasch, three-parameter, and equipercentile equating methods were compared. Six equating cases, using different sets of item parameters, were replicated based on examinee samples of low, medium, or high ability or where ability was matched to the difficulty level of the test. The results showed that all three methods were reasonably invariant to examinee ability level under all conditions imposed. This suggests that multidimensionality is likely to be the cause of the lack of invariance found in real datasets. Index terms: Examinee ability; Invariance in item response theory; Item response theory, equating; Item response theory, invariance; Test equating; Vertical equating.
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    An exploration of the robustness of four test equating models
    (1986) Skaggs, Gary; Lissitz, Robert W.
    This monte carlo study explored how four commonly used test equating methods (linear, equipercentile, and item response theory methods based on the Rasch and three-parameter models) responded to tests of different psychometric properties. The four methods were applied to generated data sets where mean item difficulty and discrimination as well as level of chance scoring were manipulated. In all cases, examinee ability was matched to the level of difficulty of the tests. The results showed the Rasch model not to be very robust to violations of the equal discrimination and non-chance scoring assumptions. There were also problems with the three-parameter model, but these were due primarily to estimation and linking problems. The recommended procedure for tests similar to those studied is the equipercentile method.