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- W3193670671 abstract "Equating test scores from nonequivalent groups requires to separate the effect of differences in ability from differences in test form difficulty between the test forms. The gold standard for this purpose is to use common items, however, not all testing programs have such items available. There might be other useful information available, and this paper studies the use of covariates in equating as a substitute for common items. To gain further insight about how to best incorporate covariates in equating this paper studies the propensity score, a scalar function of the covariates. The sensitivity of the propensity score as a proxy for ability is studied to investigate if bias is introduced in the estimated equated scores if the propensity score estimation model is misspecified. By considering an incorrect link function, leaving out a covariate and leaving out a second-order term from the estimation model, common misspecifications are studied. The results show that equating with respect to the propensity score is relatively robust to model misspecification, especially modeling nonlinearity with a linear model and leaving out second-order terms." @default.
- W3193670671 created "2021-08-30" @default.
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- W3193670671 date "2021-01-01" @default.
- W3193670671 modified "2023-09-25" @default.
- W3193670671 title "Equating Nonequivalent Groups Using Propensity Scores: Model Misspecification and Sensitivity Analysis" @default.
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- W3193670671 doi "https://doi.org/10.1007/978-3-030-74772-5_17" @default.
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