The Impact of Missing Data on the Ethical Quality of a Research Study

Authored by: Craig K. Enders , Amanda C. Gottschall

Handbook of Ethics in Quantitative Methodology

Print publication date:  January  2011
Online publication date:  March  2011

Print ISBN: 9781848728547
eBook ISBN: 9780203840023
Adobe ISBN: 9781136888731

10.4324/9780203840023.ch14

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Abstract

The purpose of this chapter is to explore the impact of missing data on the ethical quality of a research study. In doing so, we borrow heavily from the work of Rosenthal (1994) and Rosenthal and Rosnow (1984). The overarching principle of Rosenthal’s (1994) work is that ethics is closely linked with the quality of a research study, such that high-quality studies are more ethically defensible than low-quality studies. Missing data pose an obvious threat to quality at the analysis stage of a study (e.g., when a researcher uses a missing data handling technique that is prone to bias), but ethical issues arise throughout the entire research process. Accordingly, we explore the linkage between quality and ethics at the design and data collection phase, the analysis phase, and the reporting phase. In doing so, we also apply Rosenthal and Rosnow’s (1984) cost–utility model to certain missing data issues (see also Rosnow & Rosenthal, Chapter 3, this volume). In this framework, the costs associated with a study (e.g., potential harm to participants, time, money, resources) are weighed against its utility (e.g., potential benefits to participants, science, or society). As it relates to ethics, a study is more defensible when its benefits exceed its costs.

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