Nominal Response Model Is Useful for Scoring Multiple-Choice Situational Judgment Tests

2018 ◽  
Vol 23 (2) ◽  
pp. 342-366 ◽  
Author(s):  
Jiyun Zu ◽  
Patrick C. Kyllonen

We evaluated the use of the nominal response model (NRM) to score multiple-choice (also known as “select the best option”) situational judgment tests (SJTs). Using data from two large studies, we compared the reliability and correlations of NRM scores with those from various classical and item response theory (IRT) scoring methods. The SJTs measured emotional management (Study 1) and teamwork and collaboration (Study 2). In Study 1 the NRM scoring method was shown to be superior in reliability and in yielding higher correlations with external measures to three classical test theory–based and four other IRT-based methods. In Study 2, only slight differences between scoring methods were observed. An explanation for the discrepancy in findings is that in cases where item keys are ambiguous (as in Study 1), the NRM accommodates that ambiguity, but in cases where item keys are clear (as in Study 2), different methods provide interchangeable scores. We characterize ambiguous and clear keys using category response curves based on parameter estimates of the NRM and discuss the relationships between our findings and those from the wisdom-of-the-crowd literature.

2017 ◽  
Vol 78 (5) ◽  
pp. 826-856 ◽  
Author(s):  
Miguel A. García-Pérez

Bock’s nominal response model (NRM) is sometimes used to identify the empirical order of response categories in polytomous items but its application tags many items as having disordered categories. Disorderly estimated categories may not reflect a true characteristic of the items but, rather, a numerically best-fitting solution possibly equivalent to other solutions with orderly estimated categories. To investigate this possibility, an order-constrained variant of the NRM was developed that enforces the preassumed order of categories on parameter estimates, for a comparison of its outcomes with those of the original unconstrained NRM. For items with ordered categories, order-constrained and unconstrained solutions should account for the data equally well even if the latter solution estimated disordered categories for some items; for items with truly disordered categories, the unconstrained solution should outperform the order-constrained solution. Criteria for this comparative analysis are defined and their utility is tested in several simulation studies with items of diverse characteristics, including ordered and disordered categories. The results demonstrate that a comparison of order-constrained and unconstrained calibrations on such criteria provides the evidence needed to determine whether category disorder estimated on some items by the original unconstrained form of the NRM is authentic or spurious. Applications of this method to assess category order in existing data sets are presented and practical implications are discussed.


2020 ◽  
pp. 014662162096574
Author(s):  
Zhonghua Zhang

Researchers have developed a characteristic curve procedure to estimate the parameter scale transformation coefficients in test equating under the nominal response model. In the study, the delta method was applied to derive the standard error expressions for computing the standard errors for the estimates of the parameter scale transformation coefficients. This brief report presents the results of a simulation study that examined the accuracy of the derived formulas and compared the performance of this analytical method with that of the multiple imputation method. The results indicated that the standard errors produced by the delta method were very close to the criterion standard errors as well as those yielded by the multiple imputation method under all the simulation conditions.


2015 ◽  
Vol 75 (6) ◽  
pp. 901-930 ◽  
Author(s):  
Kathleen Suzanne Johnson Preston ◽  
Skye N. Parral ◽  
Allen W. Gottfried ◽  
Pamella H. Oliver ◽  
Adele Eskeles Gottfried ◽  
...  

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