Quantitative and qualitative methods: : Is There an Alternative?

Forum Qualitative Sozialforschung Forum Qualitative Social Research, 2001

The importance and meanings of the contemporary debate on quantitative and qualitative methods in social sciences and management research comes out from the fact that the participants defend their ideas in the name of science. Discussions take place at different levels, from basic epistemological topics to current decisions and evaluations of scientific communities. They involve subjects about what is science and what is a scientific theory and about what are the functions of quantitative and qualitative methods and what aspects of social world can be captured by each of them. The paper will focuss on the philosophical conceptual background of the debate and it will point out that the main concepts are considered in different ways: there are different notions of science and scientific theories; quantitative methods are defined some times as non-numerical methods and some times as interpretative methods of the meanings and purposes of social actors; finally quantitative methods include measurements, mathematical models and statistical inferences, which have different basics and rules. The first part of the paper will present a short historical overview on science and method. It will comment the geometry of Euclides and the Aristotelian physics, the legitimation of quantitative methods in the scientific revolution by Galileo and the mathematical physics of Newton; the qualitative approaches of Linnaeus and Darwin; the introduction of new scales of measurement and the creation of statistics; and the positivism of August Comte. The second part of the paper will introduce the contemporary debate on positivist and interpretativist methods. It will comment the evolution of positivism, and interpretativist approaches to the science of history; the phenomenological and hermeneutical justifications of interpretative methods in sociology; the criticism of measurement theory, the structuralist methods of the French school and the legitimation of narratives in social sciences research. That background will facilitate the development of further research about the debate. Key words: Positivist, classificatory and interpretative methods; and epistemology of science.

Qualitative & Multi-Method Research, 2007

In this brief essay I will elaborate on some of the points I raised at last year's APSA panel on multi-method work. As always, I emphasize the essential complementarity of different methods. I first briefly discuss why qualitative research and formal models have much to offer each other and why scholars in each methodological tradition can gain much from a better understanding of the other tradition. I then shift to a focus on the overlooked link between qualitative and quantitative research, to argue for a reconsideration of the requirements of the inputs of quantitative research: What constitutes good data? I close with a proposal that calls for collaboration between qualitative and quantitative researchers to set new standards for the collection and use of large-N datasets.

Much of the literature on research in applied linguistics views quantitative and qualitative research as distinct entities embodying contrasting philosophies. In this paper, however, we present an example of how preliminary quantitative analyses of data can inform a qualitative discourse analysis study. Data from an online discussion forum concerning the Thai political crisis of 2010 were initially analysed quantitatively to identify keywords, word clusters, length of postings and user ratings of postings for the contributions from the opposing political factions. Each posting was also rated for level of antagonism and credibility of argumentation. These quantitative data provide an overview of the discussion forum and the patterns of discussion within it which was then used as a framework to guide the main qualitative analysis ensuring that the key revealed meanings and functions were covered in the analysis and reducing potential bias in data analysis and presentation. Introduction Mixed methods research has a long history in disciplines that attempt to explain behavior and social phenomena (Dörnyei, 2007). The practice includes a mix or qualitative and quantitative methods, a mix of quantitative methods or a mix of qualitative methods. The type of mixed methods approach that is most popular and is increasingly employed is the first, the mix of the two, which are often based on different research paradigms. Single method research is normally criticised by their opposition as inferior and insufficient. In a pure quantitative study, with the focus on theory or hypothesis testing, the researcher may not be sensitive on contextual details. Moreover, it requires a large amount of data to be able to give an effective ground. A qualitative method, on the other hand, is prone to high subjectivity of the researcher and is unlikely to be generalisable. It can only deal with a small size of data, which makes decision making of the overview and conclusive deduction an ordeal. Four models of mixed methods design are proposed including concurrent design, explanatory sequential design, exploratory sequential design and embedded sequential/concurrent designs (Creswell & Zhang, 2009). The first model, the concurrent design compares and contrasts the results between the two methods to present evidence. Second, the explanatory sequential design utilises the explanation of one set of results to support the other's. In an exploratory sequential design, one method's results are followed by the other's to strengthen the claims made, in the name of generalisability, for instance. In the last design, embedded sequential/concurrent design, a small database is made part of the big database and is used to experiment or enhance the major findings. Typically, a mixed method research deals with different types of data but it may also mean applying different methods to investigate the same data. Two dimensions of advancements that mixed methods data analyses (MMDA) have to offer can be considered as 1) the design virtue and b) research expertise. The research virtue obtained from mixed methods may refer to the strategies that are used to display trustworthiness of the research such as triangulation, complementarity, development, initiation and expansion (Green et al, 1989). In greater details, four major advantages of MMDA have been put forward (Dörnyei, 2007). First, oversimplification, decontexualisation and reduction of the quantitative analysis can be disputed by in depth meaningful qualitative analysis, while content-specificity and unrepresentativeness can be overcome by the generalisable quantitative analysis. Second, for multi-level analyses, MMDA can add more meaning by converging numbers into words and vice versa. Third, triangulation through multi-methods analyses means increasing validity of the study of the results. Fourth, a study with mixed methods analyses tends to attract more attention from the

2017

The goal of this study is to deconstruct the meanings of the terms " quantitative " and " qualitative " , usually used to characterize scientific research method, or to try to undo what seems to be a mistake: the denomination and division of quantitative or qualitative research methods. We consider that this division confuses and impoverishes the conception of knowledge or science. There are many methodological questions so plural, conflicting or not, according to the meaning of the investigated reality which, after all, is what should be discussed from the beginning to the end of the research. We add the theoretical or ideological designation of method to this discussion that for us represents another version of the same problem. To accomplish this goal, we discuss a view of science and a conception of thought.

The Psychologist, 18, 339-340., 2005

AS authors of the proposal for the recently inaugurated Qualitative Methods in Psychology Section, we would like to respond to Mark Shevlin’s letter (May 2005). Despite the adversarial tone of the letter, he does draw our attention to aspects of our proposal which the new Section may wish to develop. First, defining qualitative methods as the absence of statistical analysis allows us to capture this diverse field concisely, and we did want to encapsulate the variety of qualitative methods with their different approaches to data collection, analysis and epistemological positions. However, it may be useful to develop a more positive definition, perhaps building on the statement included in our proposal that in qualitative analysis results are expressed in words rather than numbers. Second, it would be a mistake to downplay what statistical analysis can achieve. We hope that the new Section will work to develop mutual respect between psychologists specialising in different methodologies. Third, our proposal could have been clearer in explaining the usefulness of qualitative methods in the hypothesisdevelopment stage of psychological enquiry. Clarity in such matters is essential if the new Section is to work towards greater understanding of qualitative research. Overwhelmingly, we have found our colleagues specialising in quantitative methods to have been openminded and generous in their attitude towards the new Section, and many have supported its inauguration. We are therefore optimistic that there is a general tolerance for diverse methods within British psychology and a motivation for genuine dialogue.

Medical Practice and Reviews, 2014

This article was set out to examine the allegations labeled against qualitative research by quantitative researchers. The allegations were that: it is subjective, difficult to replicate in healthcare, and this amounts to little more than anecdote, personal impression or conjecture. In attempting to resolve the allegations, this article relied on extensive literature review and examined evidence that has been put forth in support of qualitative research approach in healthcare. The article also examined the benefits and pathologies of quantitative and qualitative approaches. It is revealed that although each of the two approaches has its own strengths and weaknesses, none can ably offer practical solutions to challenges of validity and reliability in healthcare research. To mitigate such challenges, the paper rests on the use of mixed methods/triangulation so as to neutralize pathologies inherent in each approach. It is recommended that the use of triangulation should be founded on the strong basis of pragmatism. Method integration should be done skillfully and cautiously, because validity and reliability of its findings may not be guaranteed due to its susceptibility to the ontological and epistemological positions of the researcher. The paper concludes that any attempt to resolve this debate creates even more discussions and finds this third paradigm inadequate in some research circumstances. This implies that the debate is far from over.