Taking Quantitative Data Analysis out of the Positivist Era: Calling for Theory-Driven Data-Informed Analysis

Autor/in	Haardörfer, Regine
Titel	Taking Quantitative Data Analysis out of the Positivist Era: Calling for Theory-Driven Data-Informed Analysis
Quelle	In: Health Education & Behavior, 46 (2019) 4, S.537-540 (4 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Haardörfer, Regine)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1090-1981
DOI	10.1177/1090198119853536
Schlagwörter	Data Analysis; Theories; Social Science Research; Behavioral Science Research; Statistical Analysis + Suchen Sie Ihr Suchwort? Auswertung; Theory; Theorie; Social scientific research; Sozialwissenschaftliche Forschung; Statistische Analyse
Abstract	In this article, Regine Haardörfer outlines five general steps taken by good data analysts and how they need to be theory-driven data-informed. She uses these to discuss some issues and propose approaches to promote better data analysis and reporting. The proposed steps to rigorous data analysis are to: (1) create an a priori data analysis plan; (2) create an analytic sample; (3) conduct analyses according to the plan developed in Step 1; (4) perform additional analyses based on initial findings; and (5) write up findings communicating clearly which data analyses were a priori and which were added later. Add additional tables and findings to supplemental materials. In conclusion, Haardörfer emphasizes the need for conducting data analysis using a theory-driven data-informed analysis approach to advance social and behavioral science. (ERIC).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01