Typology of Analytical and Interpretational Errors in Quantitative and Qualitative Educational Research
Abstract
The purpose of this paper is to identify and to discuss major analytical and interpretational errors that occur regularly in quantitative and qualitative educational research. A comprehensive review of the literature discussing various problems was conducted. With respect to quantitative data analyses, common analytical and interpretational misconceptions are presented for data-analytic techniques representing each major member of the general linear model, including hierarchical linear modeling. Common errors associated with many of these approaches include (a) no evidence provided that statistical assumptions were checked; (b) no power/sample size considerations discussed; (c) inappropriate treatment of multivariate data; (d) use of stepwise procedures; (e) failure to report reliability indices for either previous or present samples; (f) no control for Type I error rate; and (g) failure to report effect sizes. With respect to qualitative research studies, the most common errors are failure to provide evidence for judging the dependability (i.e., reliability) and credibility (i.e., validity) of findings, generalizing findings beyond the sample, and failure to estimate and to interpret effect sizes.
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Authors retain copyright without restrictions. Unless otherwise indicated, from 2021 all articles are published under the Creative Commons CC-BY-SA license. For more information visit https://creativecommons.org/licenses/by-sa/4.0/. Articles published prior to 2021 used a CC-BY-NC-SA license.