Assessing Rasch Measurement Estimation Methods across R Packages with Yes/No Vocabulary Test Data

Autor/inn/en	Nicklin, Christopher; Vitta, Joseph P.
Titel	Assessing Rasch Measurement Estimation Methods across R Packages with Yes/No Vocabulary Test Data
Quelle	In: Language Testing, 39 (2022) 4, S.513-540 (28 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Nicklin, Christopher) ORCID (Vitta, Joseph P.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0265-5322
DOI	10.1177/02655322211066822
Schlagwörter	Programming Languages; Vocabulary Development; Language Tests; Computer Software; Applied Linguistics; Maximum Likelihood Statistics; Academic Language; Word Lists; Test Format; Test Items; Item Analysis; Measurement Techniques; English (Second Language); English for Academic Purposes; Second Language Learning; Second Language Instruction; Cross Cultural Studies; Foreign Countries; College Freshmen; Comparative Analysis; Japan; Saudi Arabia + Suchen Sie Ihr Suchwort? Wortschatzarbeit; Language test; Sprachtest; Linguistics; Linguistik; Angewandte Linguistik; Academic; Language; Languages; Akademiker; Sprache; Wissenschaftssprache; Wortliste; Testentwicklung; Test content; Testaufgabe; Itemanalyse; Messtechnik; English as second language; English; Second Language; Englisch als Zweitsprache; Zweitsprachenerwerb; Fremdsprachenunterricht; Cultural comparison; Kulturvergleich; Ausland; Studienanfänger; Saudi-Arabien
Abstract	Instrument measurement conducted with Rasch analysis is a common process in language assessment research. A recent systematic review of 215 studies involving Rasch analysis in language testing and applied linguistics research reported that 23 different software packages had been utilized. However, none of the analyses were conducted with one of the numerous R-based Rasch analysis software packages, which generally employ one of the three estimation methods: conditional maximum likelihood estimation (CMLE), joint maximum likelihood estimation (JMLE), or marginal maximum likelihood estimation (MMLE). For this study, eRm, a CMLE-based R package, was utilized to conduct a dichotomous Rasch analysis of a Yes/No vocabulary test based on the academic word list. The resulting parameters and diagnostic statistics were compared with the equivalent results from four other R-based Rasch measurement software packages and Winsteps. Finally, all of the packages were utilized in the analysis of 1000 simulated datasets to investigate the extent to which results generated from the contrasting estimation methods converged or diverged. Overall, the differences between the results produced with the three estimation methods were negligible, and the discrepancies observed between datasets were attributable to the software choice as opposed to the estimation method. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01