Unit of Analysis
A unit of analysis constitutes an object of study in research undertakings (Cole, 2018). Definition and bounding of the case may prove challenging since a number of variables and points of interest overlap and intersect within cases researches. Development of research questions, propositions for case selection, focus identification, and boundary refining has been recommended for effective establishment of the aforementioned components in the study design. Case bounding proves crucial when it comes to information acquisition and analysis management, focusing, and framing. This entails selectiveness and specificity in the identification of case parameters such as respondents, process and location, in addition to the establishment of a timeframe for investigation of the case. To be more specific, units of analyses (UoIs) are decided by research questions (Merriam, 2009; Stake, 2006; Yin, 2014). Consider, for instance, Francis, Anderson and Stokes’ 1999 research “City Markets as a Unit of Analysis in Audit Research and the Re?Examination of Big 6 Market Shares”; here, city markets were the UoI. The researchers utilized market shares of big 6 companies on the basis of aggregate national-level data for inferring industry expertise and market leadership, besides distinguishing the big 6 accounting companies from each other.
Incorrect Unit of Analysis
Ecological fallacy is a widely occurring mistake one will get to witness in regards...
This happens when a researcher makes claims pertaining to a lower-level UoI on the basis of information from a higher-level UoI. In a large number of instances, this happens when making claims at the individual level, when information has been collected for the group. For instance, one may wish to gain insights into whether or not addiction to electronic gadgets is greater among students of particular campuses as compared to others. Perhaps, the various campuses across the nation have offered the figure for their respective share of gadget addicts, and this information teaches us that gadget addiction occurs more widely in campuses with business programs as compared to those without. It may subsequently be concluded that students enrolled in business programs will more likely become gadget addicts as compared to non-business pupils. But this wouldn’t be the proper conclusion as having only campus addiction rates can only facilitate conclusions on campuses; one cannot possibly find out about individual pupils of these campuses based on those statistics. Perhaps business schools’ sociology majors might be responsible for the high addiction rates there; the point being, only campus-level information cannot help us gain insights into individual enrollee behavior and making such conclusions on students when the information collected pertains to campuses gives rise to ecological fallacy risks (Open Textbooks, 2016).
The second potential error…
