Dissertation Data Analysis Plan
While the conventional practice is to establish a standard of acceptability for statistical significance, with certain disciplines, it may also be appropriate to discuss whether attaining statistical significance has a true practical meaning, i.e., ‘clinical significance’. Jeans (1992) defines ‘clinical significance’ as “the potential for research findings to make a real and important difference to clients or clinical practice, to health status or to any other problem identified as a relevant priority for the discipline”. Indeed, a single course in biostatistics is the most that is usually offered (Christopher Williams, cited in Nowak, 1994).
For example, Schroder, Carey, and Vanable (2003) juxtapose their identification of new and powerful data analytic solutions developed to count data in the area of HIV contraction risk with a discussion of the limitations of commonly applied methods. Improper statistical analyses distort scientific findings, mislead casual readers (Shepard, 2002), and may negatively influence the public perception of research.Integrity issues are just as relevant to analysis of non-statistical data as well.The form of the analysis is determined by the specific qualitative approach taken (field study, ethnography content analysis, oral history, biography, unobtrusive research) and the form of the data (field notes, documents, audiotape, videotape).An essential component of ensuring data integrity is the accurate and appropriate analysis of research findings.When failing to demonstrate statistically different levels between treatment groups, investigators may resort to breaking down the analysis to smaller and smaller subgroups in order to find a difference.Although this practice may not inherently be unethical, these analyses should be proposed before beginning the study even if the intent is exploratory in nature.Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data.According to Shamoo and Resnik (2003) various analytic procedures “provide a way of drawing inductive inferences from data and distinguishing the signal (the phenomenon of interest) from the noise (statistical fluctuations) present in the data”..A tacit assumption of investigators is that they have received training sufficient to demonstrate a high standard of research practice.Unintentional ‘scientific misconduct' is likely the result of poor instruction and follow-up.