000759953 000__ 04860cam\a2200505Ii\4500 000759953 001__ 759953 000759953 005__ 20230306141941.0 000759953 006__ m\\\\\o\\d\\\\\\\\ 000759953 007__ cr\cn\nnnunnun 000759953 008__ 160809s2016\\\\sz\\\\\\o\\\\\100\0\eng\d 000759953 020__ $$a9783319387598$$q(electronic book) 000759953 020__ $$a3319387596$$q(electronic book) 000759953 020__ $$z9783319387574 000759953 035__ $$aSP(OCoLC)ocn956376369 000759953 035__ $$aSP(OCoLC)956376369 000759953 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dYDXCP$$dGW5XE$$dOCLCO$$dN$T$$dIDEBK$$dOCLCO$$dEBLCP$$dOCLCF$$dOCLCO 000759953 049__ $$aISEA 000759953 050_4 $$aBF39$$b.P79 2015eb 000759953 08204 $$a150.1/5195$$223 000759953 1102_ $$aPsychometric Society.$$bAnnual Meeting$$n(80th :$$d2015 :$$cBeijing, China) 000759953 24510 $$aQuantitative psychology research$$h[electronic resource] :$$bthe 80th Annual Meeting of the Psychometric Society, Beijing, 2015 /$$cL. Andries van der Ark, Daniel M. Bolt, Wen-Chung Wang, Jeffrey A. Douglas, Marie Wiberg, editors. 000759953 264_1 $$aSwitzerland :$$bSpringer,$$c2016. 000759953 300__ $$a1 online resource. 000759953 336__ $$atext$$btxt$$2rdacontent 000759953 337__ $$acomputer$$bc$$2rdamedia 000759953 338__ $$aonline resource$$bcr$$2rdacarrier 000759953 4901_ $$aSpringer proceedings in mathematics & statistics ;$$vvolume 167 000759953 5050_ $$aPreface; Contents; Continuation Ratio Model in Item Response Theory and Selection of Models for Polytomous Items; 1 Introduction; 2 The Continuation Ratio Model and Parameter Estimation; 3 An Illustration; 4 Comparisons of Polytomous Models; 5 Discussion; Appendix; References; Using the Asymmetry of Item Characteristic Curves (ICCs) to Learn About Underlying Item Response Processes; 1 Introduction; 1.1 Other Implications of Ignoring Asymmetry in ICCs; 1.2 Item Response Processes and Asymmetric ICCs; 2 Molenaar's Normal Ogive RH Model 000759953 5058_ $$a2.1 Bayesian Estimation of Heteroscedastic Two-Parameter and Three-Parameter Normal Ogive Models3 Simulation Study; 3.1 Low Complexity Disjunctive Items: A Two Subprocess Model; 3.2 Moderate Complexity Items: One Subprocess Model; 3.3 Moderately High Complexity Conjunctive Items: A Two Subprocess Model; 3.4 High Complexity Conjunctive Items: A Five Subprocess Model; 4 Simulation Results; 5 Discussion; References; A Three-Parameter Speeded Item Response Model: Estimation and Application; 1 Introduction; 2 Leave-the-Harder-till-Later Speeded Three-Parameter Logistic Item Response Model 000759953 5058_ $$a3 Simulation Study4 Application; 5 Concluding Remarks; References; An Application of a Random Mixture Nominal Item Response Model for Investigating Instruction Effects; 1 Introduction; 2 A Random Item Mixture Nominal Response Model; 3 Simulation Study; 3.1 Simulation Design; 3.2 Simulation Study Results; 4 Empirical Study: Instruction Effects on Students' Fractions Computation; 4.1 Data Description; 4.2 Model Estimation; 4.3 Results; 4.3.1 Characteristics of Latent Classes; 4.3.2 Instruction Effects; 5 Conclusion and Discussions; References 000759953 5058_ $$aItem Response Theory Models for Multidimensional Ranking Items1 The Rasch Ipsative Model for Multidimensional Pairwise-Comparison Items; 2 Item Response Models for Multidimensional Ranking Items; 2.1 The Exploded Logit IRT; 2.2 The Generalized Logit IRT; 3 Simulations; 4 An Empirical Example; 5 Summary and Discussion; References; Different Growth Measures on Different Vertical Scales; 1 Properties of Vertical Scales; 2 A Few Growth Measures and Their Relationships; 2.1 Simple Gain and Residual Gain Scores; 2.2 Three CSPR Measures; 2.3 Scale Dependency of the Growth Measures 000759953 5058_ $$a3 Vertical Scales and the Relationships Among the Growth Measures3.1 Two Vertical Scaling Examples; 3.2 Empirical Data Comparison; 4 Conclusion and Discussion; References; Investigation of Constraint-Weighted Item Selection Procedures in Polytomous CAT; 1 Introduction; 1.1 The Maximum Priority Index (MPI) Method; 2 Method; 2.1 Simulation Study; 2.2 Evaluation Criteria; 3 Results; 4 Discussion; References; Estimating Classification Accuracy and Consistency Indices for Multidimensional Latent Ability; 1 Introduction; 2 Model and Methods; 2.1 A Multidimensional Graded Response Model 000759953 506__ $$aAccess limited to authorized users. 000759953 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 10, 2016). 000759953 650_0 $$aPsychometrics$$vCongresses. 000759953 7001_ $$aArk, L. Andries van der,$$eeditor. 000759953 7001_ $$aBolt, Daniel,$$eeditor. 000759953 7001_ $$aWang, Wen-Chung$$c(Professor of Educational and Psychological Measurement),$$eeditor. 000759953 7001_ $$aDouglas, Jeffrey A.$$eeditor. 000759953 7001_ $$aWiberg, Marie,$$eeditor. 000759953 830_0 $$aSpringer proceedings in mathematics & statistics ;$$vv. 167. 000759953 852__ $$bebk 000759953 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-38759-8$$zOnline Access$$91397441.1 000759953 909CO $$ooai:library.usi.edu:759953$$pGLOBAL_SET 000759953 980__ $$aEBOOK 000759953 980__ $$aBIB 000759953 982__ $$aEbook 000759953 983__ $$aOnline 000759953 994__ $$a92$$bISE