Missing Data Treatments in Intervention Studies: What Was, What Is, and What Should Be

Autor/inn/en	Rioux, Charlie; Little, Todd D.
Titel	Missing Data Treatments in Intervention Studies: What Was, What Is, and What Should Be
Quelle	In: International Journal of Behavioral Development, 45 (2021) 1, S.51-58 (8 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Rioux, Charlie) ORCID (Little, Todd D.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0165-0254
DOI	10.1177/0165025419880609
Schlagwörter	Prevention; Intervention; Data Analysis; Correlation; Bias; Maximum Likelihood Statistics; Outcomes of Treatment; Medical Research; Research Problems + Suchen Sie Ihr Suchwort? Prävention; Vorbeugung; Auswertung; Korrelation; Forschungskritik
Abstract	Missing data are ubiquitous in studies examining preventive interventions. This missing data need to be handled appropriately for data analyses to yield unbiased results. After a brief discussion of missing data mechanisms, inappropriate missing data treatments and appropriate missing data treatments, we review the current state of missing data treatments in intervention studies as well as how they have evolved over the years. Although missing data treatments have improved over the years, antiquated missing data treatments associated with biased results are still prevalent. Furthermore, many studies do not appropriately report their rates of missing data and missing data treatments. Using appropriate missing data treatments is elemental to accurately identify effective preventive interventions and properly inform practice and policy. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01