Modeling of Item Response Functions Under the D-Scoring Method.This study presents new models for item response functions (IRFs) in the framework of the D-scoring method (DSM) that is gaining attention in the field of educational and psychological measurement and largescale assessments.  In a previous work on DSM, the IRFs of binary items were estimated using a logistic regression model (LRM).  The inverse-regression adjustments used to fix this problem are too complicated for regular applications of the DSM and not in line with its simplicity. 
DSM
In a previous work on DSM, the IRFs of binary items were estimated using a logistic regression model (LRM).  However, the LRM underestimates the item true scores at the top end of the D-scale (ranging from 0 to 1), especially for relatively difficult items. 
LRM
This issue is resolved with the IRF models proposed in this study, referred to as rational function models (RFMs) with one parameter (RFM1), two parameters (RFM2), and three parameters (RFM3). 
RFM1
This issue is resolved with the IRF models proposed in this study, referred to as rational function models (RFMs) with one parameter (RFM1), two parameters (RFM2), and three parameters (RFM3). 
RFM2
This issue is resolved with the IRF models proposed in this study, referred to as rational function models (RFMs) with one parameter (RFM1), two parameters (RFM2), and three parameters (RFM3). 
RFM3