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Browsing by Author "McLaughlin, Mary E."

Now showing 1 - 4 of 4
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    Appropriateness measurement for some multidimensional test batteries
    (1991) Drasgow, Fritz; Levine, Michael V.; McLaughlin, Mary E.
    Model-based methods for the detection of individuals inadequately measured by a test have generally been limited to unidimensional tests. Extensions of unidimensional appropriateness indices are developed here for multi-unidimensional tests (i.e., multidimensional tests composed of unidimensional subtests). Simulated and real data were used to evaluate the effectiveness of the multitest appropriateness indices. Very high rates of detection of spuriously high and spuriously low response patterns were obtained with the simulated data. These detection rates were comparable to rates obtained for long unidimensional tests (both simulated and real) with approximately the same number of items. For real data, similarly high detection rates were obtained in the spuriously high condition; slightly lower detection rates were observed for the spuriously low condition. Several directions for future research are described. Index terms: appropriateness measurement, item response theory, multidimensional tests, optimal appropriateness measurement, polychotomous measurement.
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    Detecting inappropriate test scores with optimal and practical appropriateness indices
    (1987) Drasgow, Fritz; Levine, Michael V.; McLaughlin, Mary E.
    Several statistics have been proposed as quantitative indices of the appropriateness of a test score as a measure of ability. Two criteria have been used to evaluate such indices in previous research. The first criterion, standardization, refers to the extent to which the conditional distributions of an index, given ability, are invariant across ability levels. The second criterion, relative power, refers to indices’ relative effectiveness for detecting inappropriate test scores. In this paper the effectiveness of nine appropriateness indices is determined in an absolute sense by comparing them to optimal indices; an optimal index is the most powerful index for a particular form of aberrance that can be computed from item responses. Three indices were found to provide nearly optimal rates of detection of very low ability response patterns modified to simulate cheating, as well as very high ability response patterns modified to simulate spuriously low responding. Optimal indices had detection rates from 50% to 200% higher than any other index when average ability response vectors were manipulated to appear spuriously high and spuriously low.
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    Lord's chi-square test of item bias with estimated and with known person parameters
    (1987) McLaughlin, Mary E.; Drasgow, Fritz
    Properties of Lord’s chi-square test of item bias were studied in a computer simulation. 0 parameters were drawn from a standard normal distribution and responses to a 50-item test were generated using SAT-v item parameters estimated by Lord. One hundred independent samples were generated under each of the four combinations of two sample sizes (N = 1,000 and N = 250) and two logistic models (two- and three-parameter). LOGIST was used to estimate item and person parameters simultaneously. For each of the 50 items, 50 independent chi-square tests of the equality of item parameters were calculated. Proportions of significant chi-squares were calculated over items and samples, at alpha levels of .0005, .001, .005, .01, .05, and .10. The overall proportions significant were as high as 11 times the nominal alpha level. The proportion significant for some items was as high as .32 when the nominal alpha level was .05. When person parameters were held fixed at their true values and only item parameters were estimated, the actual rejection rates were close to the nominal rates.
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    Modeling incorrect responses to multiple-choice items with multilinear formula score theory
    (1989) Drasgow, Fritz; Levine, Michael V.; Williams, Bruce; McLaughlin, Mary E.; Candell, Gregory L.
    Multilinear formula score theory (Levine, 1984, 1985, 1989a, 1989b) provides powerful methods for addressing important psychological measurement problems. In this paper, a brief review of multilinear formula scoring (MFS) is given, with specific emphasis on estimating option characteristic curves (OCCS). MFS was used to estimate OCCS for the Arithmetic Reasoning subtest of the Armed Services Vocational Aptitude Battery. A close match was obtained between empirical proportions of option selection for examinees in 25 ability intervals and the modeled probabilities of option selection. In a second analysis, accurately estimated OCCS were obtained for simulated data. To evaluate the utility of modeling incorrect responses to the Arithmetic Reasoning test, the amounts of statistical information about ability were computed for dichotomous and polychotomous scorings of the items. Consistent with earlier studies, moderate gains in information were obtained for low to slightly above average abilities. Index terms: item response theory, marginal maximum likelihood estimation, maximum likelihood estimation, multilinear formula scoring, option characteristic curves, polychotomous measurement, test information function.