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  • Search: person:"Sinharay, Sandip"
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2PL model 2 2-parameter-logistic model 1 Befragung 1 Data collection 1 Datenerhebung 1 IRT model fit 1 IRT observed-score equating 1 Interview 1 Market research 1 Marktforschung 1 Mean squared error 1 Rasch model 1 Statistical error 1 Statistischer Fehler 1 augmented subscore 1 chain equating 1 cumulant generating function 1 frequency estimation 1 generalized partial credit model 1 item characteristic curve 1 item response theory 1 latent regression 1 normal ogive model 1 post-stratification equating 1 raking 1 simulation 1 stochastic EM 1 stochastic approximation 1 true equating function 1
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Undetermined 6
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Article 7
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Aufsatz im Buch 1 Book section 1
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Undetermined 6 English 1
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Sinharay, Sandip 7 Haberman, Shelby 3 Holland, Paul 2 Chon, Kyong 1 Davier, Matthias von 1 Haberman, Shelby J. 1 Vriens, Marco 1
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Psychometrika 4 Journal of Educational and Behavioral Statistics 1 Journal of the American Statistical Association 1 The handbook of marketing research : uses, misuses, and future advances 1
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RePEc 6 ECONIS (ZBW) 1
Showing 1 - 7 of 7
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Assessing Item Fit for Unidimensional Item Response Theory Models Using Residuals from Estimated Item Response Functions
Haberman, Shelby; Sinharay, Sandip; Chon, Kyong - In: Psychometrika 78 (2013) 3, pp. 417-440
Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, <CitationRef CitationID="CR20">1985</CitationRef>; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, <CitationRef CitationID="CR21">1991</CitationRef>) is a popular method to assess fit of item response theory (IRT)...</citationref></citationref>
Persistent link: https://www.econbiz.de/10010998747
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Generalized Residuals for General Models for Contingency Tables With Application to Item Response Theory
Haberman, Shelby J.; Sinharay, Sandip - In: Journal of the American Statistical Association 108 (2013) 504, pp. 1435-1444
Generalized residuals are a tool employed in the analysis of contingency tables to examine possible sources of model error. They have typically been applied to log-linear models and to latent-class models. A general approach to generalized residuals is developed for a very general class of...
Persistent link: https://www.econbiz.de/10010824040
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Reporting of Subscores Using Multidimensional Item Response Theory
Haberman, Shelby; Sinharay, Sandip - In: Psychometrika 75 (2010) 2, pp. 209-227
Persistent link: https://www.econbiz.de/10008456056
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The Missing Data Assumptions of the NEAT Design and their Implications for Test Equating
Sinharay, Sandip; Holland, Paul - In: Psychometrika 75 (2010) 2, pp. 309-327
Persistent link: https://www.econbiz.de/10008456058
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Stochastic Approximation Methods for Latent Regression Item Response Models
Davier, Matthias von; Sinharay, Sandip - In: Journal of Educational and Behavioral Statistics 35 (2010) 2, pp. 174-193
This article presents an application of a stochastic approximation expectation maximization (EM) algorithm using a Metropolis-Hastings (MH) sampler to estimate the parameters of an item response latent regression model. Latent regression item response models are extensions of item response...
Persistent link: https://www.econbiz.de/10010776004
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Limits on Log Odds Ratios for Unidimensional Item Response Theory Models
Haberman, Shelby; Holland, Paul; Sinharay, Sandip - In: Psychometrika 72 (2007) 4, pp. 551-561
Persistent link: https://www.econbiz.de/10005757977
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Dealing with missing data in surveys and databases
Vriens, Marco; Sinharay, Sandip - In: The handbook of marketing research : uses, misuses, and …, (pp. 178-191). 2006
Persistent link: https://www.econbiz.de/10003420112
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