000			04114nam a22004453i 4500
001			EBC5752263
003			MiAaPQ
005			20240724113645.0
006			m o d |
007			cr cnu||||||||
008			240724s2019 xx o ||||0 eng d
020			_a9788024639840 _q(electronic bk.)
020			_z9788024639185
035			_a(MiAaPQ)EBC5752263
035			_a(Au-PeEL)EBL5752263
035			_a(OCoLC)1099319894
040			_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ
050		4	_aLB3060.32.C65 .K663 2019
082	0		_a371.260285
100	1		_aKomarc, Martin.
245	1	0	_aComputerized Adaptive Testing in Kinanthropology : _bMonte Carlo Simulations Using the Physical Self-Description Questionnaire.
250			_a1st ed.
264		1	_aPrague : _bKarolinum Press, _c2019.
264		4	_c©2019.
300			_a1 online resource (132 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
505	0		_aCover -- Contents -- Acknowledgements -- 1. Brief introductionto measurement(in Kinanthropology) -- 2. Historical Pathsto Modern Test Theory -- 3. Groundwork forItem Response Theory -- 4. Item Response Theory (IRT) -- 4.1 Introduction -- 4.2 Unidimensional dichotomous IRT models -- 4.3 Unidimensional polytomous IRT models -- 4.4 Assumptions required for unidimensional IRT models -- 4.5 Parameter estimation in IRT models -- 4.5.1 Latent trait (θ) estimation -- 4.5.2 Item parameters estimation -- 4.6 Information and standard error of the θ estimates -- 5. Computerized AdaptiveTesting (CAT): Historicaland conceptual origins -- 6. Testing algorithmsin unidimensionalIRT-based CAT -- 6.1 Starting -- 6.2 Continuing -- 6.3 Stopping -- 6.4 Practical issues related to item selection in CAT -- 6.4.1 Item pool -- 6.4.2 Content balancing -- 6.4.3 Exposure control -- 6.5 Evaluation of item selection and trait estimation methodsused in computerized adaptive testing algorithms -- 7. Empirical part -problem statement -- 8. Aims and hypotheses -- 9. Methods -- 9.1 Item pool, IRT model used for item calibration,dimensionality analysis -- 9.1.1 General description of the item pool -- 9.1.2 Item calibration -- 9.1.3 Dimensionality analysis -- 9.2 CAT simulation design and specifications -- 9.2.1 Step 1. Simulate latent trait values (true θ) -- 9.2.2 Step 2. Supply item parameters for the intended item pool -- 9.2.3 Step 3. Set CAT algorithm options -- 9.2.4 Step 4. Simulate CAT administration -- 9.3 Analysis of simulation results -- 10. Results -- 10.1 Dimensionality -- 10.2 Number of administered items in CAT simulation -- 10.3 Bias of the CAT latent trait estimates -- 10.4 Correlations -- 11. Discussion -- 12. Conclusions -- Summary -- References -- Appendices.
505	8		_aAppendix A - IRT parameters (a - discrimination and b's -thresholds) for the Physical Self-Description Questionnaireitems (source: Flatcher &amp -- Hattie, 2004) -- Appendix B - R code used for the simulation of the PSDQ CAT -- Appendix C - Test information and corresponding standarderror for the Physical Self-Description Questionnaireitem pool -- Appendix D - Example of R code used to create Figure 1 -- Appendix E - Online application for adaptive testing usingthe Physical Self-Description Questionnaire -- List of Tables -- List of Figures.
588			_aDescription based on publisher supplied metadata and other sources.
590			_aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
650		0	_aComputer adaptive testing.
650		0	_aAnthropology.
650		0	_aItem response theory.
655		4	_aElectronic books.
776	0	8	_iPrint version: _aKomarc, Martin _tComputerized Adaptive Testing in Kinanthropology: Monte Carlo Simulations Using the Physical Self-Description Questionnaire _dPrague : Karolinum Press,c2019 _z9788024639185
797	2		_aProQuest (Firm)
856	4	0	_uhttps://ebookcentral.proquest.com/lib/orpp/detail.action?docID=5752263 _zClick to View
999			_c9950 _d9950