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Review of psychology, Vol.16 No.2 Prosinac 2009.

Izvorni znanstveni članak

Questionnaire design considerations with planned missing data

Levente Littvay ; Central European University

Puni tekst: engleski, pdf (987 KB) str. 103-114 preuzimanja: 363* citiraj
APA 6th Edition
Littvay, L. (2009). Questionnaire design considerations with planned missing data. Review of psychology, 16 (2), 103-114. Preuzeto s https://hrcak.srce.hr/70642
MLA 8th Edition
Littvay, Levente. "Questionnaire design considerations with planned missing data." Review of psychology, vol. 16, br. 2, 2009, str. 103-114. https://hrcak.srce.hr/70642. Citirano 22.10.2018.
Chicago 17th Edition
Littvay, Levente. "Questionnaire design considerations with planned missing data." Review of psychology 16, br. 2 (2009): 103-114. https://hrcak.srce.hr/70642
Harvard
Littvay, L. (2009). 'Questionnaire design considerations with planned missing data', Review of psychology, 16(2), str. 103-114. Preuzeto s: https://hrcak.srce.hr/70642 (Datum pristupa: 22.10.2018.)
Vancouver
Littvay L. Questionnaire design considerations with planned missing data. Review of psychology [Internet]. 19.12.2009. [pristupljeno 22.10.2018.];16(2):103-114. Dostupno na: https://hrcak.srce.hr/70642
IEEE
L. Littvay, "Questionnaire design considerations with planned missing data", Review of psychology, vol.16, br. 2, str. 103-114, prosinac 2009. [Online]. Dostupno na: https://hrcak.srce.hr/70642. [Citirano: 22.10.2018.]

Sažetak
This article explores considerations that emerge when using a planned missing data design (PMDD). It describes scenarios where a PMDD can be useful and reveals implications of a PMDD for questionnaire design in terms of the optimal number of questionnaire versions. It takes a confirmatory factor model to explore the PMDD performance. Findings suggest that increasing the number of versions to maximize uniformity of missing data yields no advantage over minimizing data collection cost and complexity. The paper makes recommendations concerning different missing data patterns that can be used. And finally, this article points out how certain fit statistics could be misleading with PMDD. The one fit statistics that consistently performed well with the PMDD is the SRMR.

Ključne riječi
planned missing data; pattern of missing data; confirmatory factor analysis; fit statistic; Monte Carlo

Hrčak ID: 70642

URI
https://hrcak.srce.hr/70642

Posjeta: 510 *