Repozytorium Uniwersytetu Jagiellońskiego

The handling of missing binary data in language research

The handling of missing binary data in language research

Metadane (Dublin Core)

dc.contributor.author Pichette, François pl
dc.contributor.author Béland, Sébastien pl
dc.contributor.author Jolani, Shahab pl
dc.contributor.author Leśniewska, Justyna [SAP11018454] pl
dc.date.accessioned 2015-07-03T10:49:47Z
dc.date.available 2015-07-03T10:49:47Z
dc.date.issued 2015 pl
dc.identifier.issn 2083-5205 pl
dc.identifier.uri http://ruj.uj.edu.pl/xmlui/handle/item/11432
dc.language eng pl
dc.rights Dodaję tylko opis bibliograficzny *
dc.rights.uri *
dc.title The handling of missing binary data in language research pl
dc.type JournalArticle pl
dc.description.physical 153-169 pl
dc.description.additional Bibliogr. s. 167-169 pl
dc.abstract.en Researchers are frequently confronted with unanswered questions or items on their questionnaires and tests, due to factors such as item difficulty, lack of testing time, or participant distraction. This paper first presents results from a poll confirming previous claims (Rietveld & van Hout, 2006; Schafer & Graham, 2002) that data replacement and deletion methods are common in research. Language researchers declared that when faced with missing answers of the yes/no type (that translate into zero or one in data tables), the three most common solutions they adopt are to exclude the participant’s data from the analyses, to leave the square empty, or to fill in with zero, as for an incorrect answer. This study then examines the impact on Cronbach’s α of five types of data insertion, using simulated and actual data with various numbers of participants and missing percentages. Our analyses indicate that the three most common methods we identified among language researchers are the ones with the greatest impact on Cronbach's α coefficients; in other words, they are the least desirable solutions to the missing data problem. On the basis of our results, we make recommendations for language researchers concerning the best way to deal with missing data. Given that none of the most common simple methods works properly, we suggest that the missing data be replaced either by the item’s mean or by the participants’ overall mean to provide a better, more accurate image of the instrument’s internal consistency. pl
dc.subject.en missing data pl
dc.subject.en Cronbach’s alpha pl
dc.subject.en participant exclusion pl
dc.subject.en second language testing pl
dc.description.volume 5 pl
dc.description.number 1 pl
dc.description.publication 1 pl
dc.identifier.doi 10.14746/ssllt.2015.5.1.8 pl
dc.identifier.eissn 2084-1965 pl
dc.title.journal Studies in Second Language Learning and Teaching pl
dc.language.container eng pl
dc.affiliation Wydział Filologiczny : Instytut Filologii Angielskiej pl
dc.subtype Article pl
dc.rights.original CC-BY-NC; otwarte czasopismo; ostateczna wersja wydawcy; w momencie opublikowania; 0; pl
.pointsMNiSW [2015 B]: 13


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