Multidimensional Rasch Models for Partial - Credit Scoring
نویسنده
چکیده
منابع مشابه
Measures of Partial Knowledge and Unexpected Responses in Multiple-Choice Tests
This study investigates differences in the partial scoring performance of examinees in elimination testing and conventional dichotomous scoring of multiple-choice tests implemented on a computer-based system. Elimination testing that uses the same set of multiple-choice items rewards examinees with partial knowledge over those who are simply guessing. This study provides a computer-based test a...
متن کاملInvestigating the missing data effect on credit scoring rule based models: The case of an Iranian bank
Credit risk management is a process in which banks estimate probability of default (PD) for each loan applicant. Data sets of previous loan applicants are built by gathering their data, and these internal data sets are usually completed using external credit bureau’s data and finally used for estimating PD in banks. There is also a continuous interest for bank to use rule based classifiers to b...
متن کاملplink: An R Package for Linking Mixed-Format Tests Using IRT-Based Methods
This introduction to the R package plink is a (slightly) modified version of Weeks (2010), published in the Journal of Statistical Software. The R package plink has been developed to facilitate the linking of mixed-format tests for multiple groups under a common item design using unidimensional and multidimensional IRT-based methods. This paper presents the capabilities of the package in the co...
متن کاملHow Good Is „Good“ ? - Making Better Use of Subjective Information in Bank Internal Credit Scoring Systems
Lenders experience positive net revenue impacts from lending if they increase the classification power of their credit scoring systems. If loan officers’ subjective assessments of otherwise intangible borrower characteristics contain additional information about a borrower, a lender may improve the default forecast quality of his internal credit scoring systems by utilizing this subjective info...
متن کاملA general diagnostic model applied to language testing data.
Probabilistic models with one or more latent variables are designed to report on a corresponding number of skills or cognitive attributes. Multidimensional skill profiles offer additional information beyond what a single test score can provide, if the reported skills can be identified and distinguished reliably. Many recent approaches to skill profile models are limited to dichotomous data and ...
متن کامل