Improvement of Norm Score Quality via Regression-Based Continuous Norming

Autor/inn/en	Lenhard, Wolfgang; Lenhard, Alexandra
Titel	Improvement of Norm Score Quality via Regression-Based Continuous Norming
Quelle	In: Educational and Psychological Measurement, 81 (2021) 2, S.229-261 (33 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Lenhard, Wolfgang)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164420928457
Schlagwörter	Test Norms; Scores; Regression (Statistics); Test Items; Difficulty Level; Item Response Theory; Comparative Analysis; Sample Size; Goodness of Fit; Age; Statistical Analysis; Psychometrics; Raw Scores + Suchen Sie Ihr Suchwort? Testnorm; Regression; Regressionsanalyse; Test content; Testaufgabe; Schwierigkeitsgrad; Item-Response-Theorie; Alter; Lebensalter; Statistische Analyse; Psychometry; Psychometrie
Abstract	The interpretation of psychometric test results is usually based on norm scores. We compared semiparametric continuous norming (SPCN) with conventional norming methods by simulating results for test scales with different item numbers and difficulties via an item response theory approach. Subsequently, we modeled the norm scores based on random samples with varying sizes either with a conventional ranking procedure or SPCN. The norms were then cross-validated by using an entirely representative sample of N = 840,000 for which different measures of norming error were computed. This process was repeated 90,000 times. Both approaches benefitted from an increase in sample size, with SPCN reaching optimal results with much smaller samples. Conventional norming performed worse on data fit, age-related errors, and number of missings in the norm tables. The data fit in conventional norming of fixed subsample sizes varied with the granularity of the age brackets, calling into question general recommendations for sample sizes in test norming. We recommend that test norms should be based on statistical models of the raw score distributions instead of simply compiling norm tables via conventional ranking procedures. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01