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Performance of longitudinal item response theory models in shortened or partial assessments.


ABSTRACT: This work evaluates the performance of longitudinal item response (IR) theory models in shortened assessments using an existing model for part II and III of the MDS-UPDRS score. Based on the item information content, the assessment was reduced by removal of items in multiple increments and the models' ability to recover the item characteristics of the remaining items at each level was evaluated. This evaluation was done for both simulated and real data. The metric of comparison in both cases was the item information function. For real data, the impact of shortening on the estimated disease progression and drug effect was also studied. In the simulated data setting, the item characteristics did not differ between the full and the shortened assessments down to the lowest level of information remaining; indicating a considerable independence between items. In contrast when reducing the assessment in a real data setting, a substantial change in item information was observed for some of the items. Disease progression and drug effect estimates also decreased in the reduced assessments. These changes indicate a shift in the measured construct of the shortened assessment and warrant caution when comparing results from a partial assessment with results from the full assessment.

SUBMITTER: Arrington L 

PROVIDER: S-EPMC7520414 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Performance of longitudinal item response theory models in shortened or partial assessments.

Arrington Leticia L   Ueckert Sebastian S   Ahamadi Malidi M   Macha Sreeraj S   Karlsson Mats O MO  

Journal of pharmacokinetics and pharmacodynamics 20200702 5


This work evaluates the performance of longitudinal item response (IR) theory models in shortened assessments using an existing model for part II and III of the MDS-UPDRS score. Based on the item information content, the assessment was reduced by removal of items in multiple increments and the models' ability to recover the item characteristics of the remaining items at each level was evaluated. This evaluation was done for both simulated and real data. The metric of comparison in both cases was  ...[more]

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