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007 | he u||024|||| | ||
008 | 080220s1982 xxu ||| bt ||| | eng d | ||
037 |
_aED264268 _bERIC |
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040 |
_aericd _beng _cericd _dMvI _dBD-DhUL |
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091 | _amfm | ||
100 | 1 | _aDrasgow, Fritz. | |
245 | 1 | 0 |
_aApplication of Unidimensional Item Response Theory Models to Multidimensional Data _h[microform] / _cFritz Drasgow and Charles K. Parsons. |
260 |
_a[Washington, D.C.] : _bDistributed by ERIC Clearinghouse, _c1982. |
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300 | _a16 p. | ||
500 |
_aERIC Note: In: Item Response Theory and Computerized Adaptive Testing Conference Proceedings (Wayzata, MN, July 27-30, 1982) (TM 850 744). _5ericd |
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520 | _aThe effects of a multidimensional latent trait space on estimation of item and person parameters by the computer program LOGIST are examined. Several item pools were simulated that ranged from truly unidimensional to an inconsequential general latent trait. Item pools with intermediate levels of prepotency of the general latent trait were also constructed. These item pools were used to determine the degree of prepotency that is required by LOGIST in order to recover the general latent trait and not be drawn to a latent trait underlying a cluster of items. The types of multidimensionality studied have several effects on the estimation techniques programmed in LOGIST. Perhaps most important is that as the prepotency of the general factor decreases, LOGIST is gradually drawn to the strongest group factor. Estimates of item difficulty occasionally become excessively large in magnitude when actual data sets are analyzed by LOGIST, although the most recent version has options that may reduce this problem. The results obtained here indicate that this phenomenon may partially be due to multidimensional item pools. However, unidimensional models do provide a good description of multidimensional data sets when the dominant latent trait is sufficiently prepotent. (PN) | ||
521 | 8 |
_aResearchers. _bericd |
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533 |
_aMicrofiche. _b[Washington D.C.]: _cERIC Clearinghouse _emicrofiches : positive. |
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650 | 1 | 7 |
_aComputer Simulation. _2ericd |
650 | 0 | 7 |
_aComputer Software. _2ericd |
650 | 0 | 7 |
_aDifficulty Level. _2ericd |
650 | 1 | 7 |
_aItem Analysis. _2ericd |
650 | 0 | 7 |
_aItem Banks. _2ericd |
650 | 1 | 7 |
_aLatent Trait Theory. _2ericd |
650 | 1 | 7 |
_aMathematical Models. _2ericd |
650 | 0 | 7 |
_aMaximum Likelihood Statistics. _2ericd |
650 | 0 | 7 |
_aPsychometrics. _2ericd |
650 | 0 | 7 |
_aTest Items. _2ericd |
650 | 0 | 7 |
_aTesting Problems. _2ericd |
653 | 1 |
_aParametric Analysis _aUnidimensional Scaling |
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653 | 0 | _aLOGIST Computer Program | |
655 | 7 |
_aReports, Research. _2ericd |
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655 | 7 |
_aSpeeches/Meeting Papers. _2ericd |
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700 | 1 |
_aParsons, Charles K., _eauthor. |
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942 |
_2ddc _cBK |
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984 |
_aANL _cmc 2253 ED264268 _d77000000269801 |
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999 |
_c124624 _d124624 |