Literature DB >> 26820428

Traditional scores versus IRT estimates on forced-choice tests based on a dominance model.

Pedro M Hontangas1, Iwin Leenen, Jimmy de la Torre, Vicente Ponsoda, Daniel Morillo, Francisco J Abad.   

Abstract

BACKGROUND: Forced-choice tests (FCTs) were proposed to minimize response biases associated with Likert format items. It remains unclear whether scores based on traditional methods for scoring FCTs are appropriate for between-subjects comparisons. Recently, Hontangas et al. (2015) explored the extent to which traditional scoring of FCTs relates to the true scores and IRT estimates. The authors found certain conditions under which traditional scores (TS) can be used with FCTs when the underlying IRT model was an unfolding model. In this study, we examine to what extent the results are preserved when the underlying process becomes a dominance model.
METHOD: The independent variables analyzed in a simulation study are: forced-choice format, number of blocks, discrimination of items, polarity of items, variability of intra-block difficulty, range of difficulty, and correlation between dimensions.
RESULTS: A similar pattern of results was observed for both models; however, correlations between TS and true thetas are higher and the differences between TS and IRT estimates are less discrepant when a dominance model involved.
CONCLUSIONS: A dominance model produces a linear relationship between TS and true scores, and the subjects with extreme thetas are better measured.

Mesh:

Year:  2016        PMID: 26820428     DOI: 10.7334/psicothema2015.204

Source DB:  PubMed          Journal:  Psicothema        ISSN: 0214-9915


  2 in total

1.  A Dominance Variant Under the Multi-Unidimensional Pairwise-Preference Framework: Model Formulation and Markov Chain Monte Carlo Estimation.

Authors:  Daniel Morillo; Iwin Leenen; Francisco J Abad; Pedro Hontangas; Jimmy de la Torre; Vicente Ponsoda
Journal:  Appl Psychol Meas       Date:  2016-08-20

2.  Computerized Adaptive Testing for Ipsative Tests with Multidimensional Pairwise-Comparison Items: Algorithm Development and Applications.

Authors:  Xue-Lan Qiu; Jimmy de la Torre; Sage Ro; Wen-Chung Wang
Journal:  Appl Psychol Meas       Date:  2022-04-14
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.