Development of a Method for Imputation of Missing Data Using ACS Exams as a Prototype

Autor/inn/en	Marek, Keith A.; Raker, Jeffrey R.; Murphy, Kristen L.
Titel	Development of a Method for Imputation of Missing Data Using ACS Exams as a Prototype
Quelle	In: Journal of Chemical Education, 96 (2019) 6, S.1083-1095 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Marek, Keith A.) ORCID (Raker, Jeffrey R.) ORCID (Murphy, Kristen L.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0021-9584
Schlagwörter	Data; Science Tests; Chemistry; Data Analysis + Suchen Sie Ihr Suchwort? Daten; Chemie; Auswertung
Abstract	Missing data is a regular issue that researchers and practitioners must consider for treatment. Commonly, cases for which data is missing are excluded from inclusion in larger data sets. However, this is not the only option and could artificially alter the sample. Other options are available for imputing missing data. Expanding on work previously reported, a method is presented here that not only preserves all observed data but also is shown to function for smaller data sets. As an example of the process, four ACS Exams are used as prototypes with a discussion on an expected noise level of any imputed sample. (As Provided).
Anmerkungen	Division of Chemical Education, Inc. and ACS Publications Division of the American Chemical Society. 1155 Sixteenth Street NW, Washington, DC 20036. Tel: 800-227-5558; Tel: 202-872-4600; e-mail: eic@jce.acs.org; Web site: http://pubs.acs.org/jchemeduc
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01