Dear experts,
I have noticed that researchers who are able to publish in first-tier journals often use advanced data analysis methods, which usually involve numerical forms such as Confirmatory Factor Analysis (CFA), Structural Equation Modelling, and Comparative Analysis.
While I acknowledge the significance of using advanced data analysis methods like CFA and structural equation modelling to answer specific research questions, I am interested to know why there is a preference for these methods over qualitative studies.
Look forward to hearing from you.
One reason may be that the analysis of data obtained in qualitative studies is more complex than in quantitative studies and that there is more subjectivity involved in the analysis of qualitative data. In addition, many (most?) phenomena in the social sciences are quantitative in nature (i.e., they can be measured on a continuum from low to high). Therefore, quantitative analysis of attributes such as intelligence, anxiety, personality, attitudes, etc. seems natural.
Well, from my experience, it is a mix of both. Sometimes, simple analytical methods produce great results that top tier editors appreciate.
It depends on how they are presented in a paper.
2ndly, complex methods may not necessarily generate the effects required except if the readership of the journal (niche) are experts .
However, a mixed method/s approach where applicable, is advised.
In conclusion, simplicity, appropriateness, and comprehensibility of your analysis and results coupled with relevant implications to practice are to key to acceptance.
I'll add that it entirely depends on the journal (topic). In some disciplines it's common to publish qualitative results. In others it's very rare.
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