Test Validation without Measurement: A Plea for Disentangling Scientific Explanation of Item Responses and Justification of Focused Assessment Policies Based on Test Data

Abstract : Test validation based on usual statistical analyses is paradoxical, as, from a falsificationist perspective, they do not test that test data are ordinal measurements, and, from the ethical perspective, they do not justify the use of test scores. This paper (i) proposes some basic definitions, where measurement is a special case of scientific explanation; starting from the examples of memory accuracy and suicidality as scored by two widely used clinical tests/questionnaires. Moreover it shows (ii) how to elicit the logic of the observable test events underlying the test scores, and (iii) how the measurability of the target theoretical quantities—memory accuracy and suicidality—can and should be tested at the respondent scale as opposed to the scale of aggregates of respondents. (iv) Criterion-related validity is revisited to stress that invoking the explanative power of test data should draw attention on counter-examples instead of statistical summarization. (v) Finally, it is argued that the justification of the use of test scores in specific settings should be part of the test validation task, because, as tests specialists, psychologists are responsible for proposing their tests for social uses.
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Pré-publication, Document de travail
2014
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Emilie Lacot, Mohammad Hassan Afzali, Stéphane Vautier. Test Validation without Measurement: A Plea for Disentangling Scientific Explanation of Item Responses and Justification of Focused Assessment Policies Based on Test Data. 2014. 〈hal-01088156〉

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