The Use of Test Scores from Large-Scale Assessment Surveys: Psychometric and Statistical Considerations

Autor/inn/en	Braun, Henry; von Davier, Matthias
Titel	The Use of Test Scores from Large-Scale Assessment Surveys: Psychometric and Statistical Considerations
Quelle	In: Large-scale Assessments in Education, 5 (2017), Artikel 17 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (von Davier, Matthias)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2196-0739
DOI	10.1186/s40536-017-0050-x
Schlagwörter	Scores; Test Use; Measurement; Psychometrics; Statistical Analysis; National Competency Tests; Achievement Tests; Foreign Countries; Elementary Secondary Education; International Assessment; Mathematics Tests; Science Tests; Mathematics Achievement; Science Achievement; Secondary School Students; Item Response Theory; Maximum Likelihood Statistics; Regression (Statistics); National Assessment of Educational Progress; Trends in International Mathematics and Science Study; Program for International Student Assessment + Suchen Sie Ihr Suchwort? Testanwendung; Messverfahren; Psychometry; Psychometrie; Statistische Analyse; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen; Ausland; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Sekundarschüler; Item-Response-Theorie; Regression; Regressionsanalyse
Abstract	Background: Economists are making increasing use of measures of student achievement obtained through large-scale survey assessments such as NAEP, TIMSS, and PISA. The construction of these measures, employing plausible value (PV) methodology, is quite different from that of the more familiar test scores associated with assessments such as the SAT or ACT. These differences have important implications both for utilization and interpretation. Although much has been written about PVs, it appears that there are still misconceptions about whether and how to employ them in secondary analyses. Methods: We address a range of technical issues, including those raised in a recent article that was written to inform economists using these databases. First, an extensive review of the relevant literature was conducted, with particular attention to key publications that describe the derivation and psychometric characteristics of such achievement measures. Second, a simulation study was carried out to compare the statistical properties of estimates based on the use of PVs with those based on other, commonly used methods. Results: It is shown, through both theoretical analysis and simulation, that under fairly general conditions appropriate use of PV yields approximately unbiased estimates of model parameters in regression analyses of large scale survey data. The superiority of the PV methodology is particularly evident when measures of student achievement are employed as explanatory variables. Conclusions: The PV methodology used to report student test performance in large scale surveys remains the state-of-the-art for secondary analyses of these databases. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01