Merits Of Quantitative And Qualitative Research Methods

Mixing methods is fairly self-explanatory, mixing both the quantitative and qualitative methods. Creswell describes this approach as involving philosophical assumptions, the use of qualitative and quantitative approaches, and the mixing of both approaches in a study. The mixed methods approach facilitates the collection of both qualitative and quantitative data in the same research project. It is up to the researcher to determine to what extent one approach is to be used over the other, and this is in the main dependent on the purpose of the study.

In looking at the issues of qualitative versus quantitative research, one needs to consider the different ‘epistemological’ and ‘technical’ arguments. For example, on first consideration the use of questionnaires in research might be seen as a quantitative strategy, whereas interviews might be thought of a qualitative technique. Similarly, it is often assumed that quantitative approaches draw on positivist ontologies whereas qualitative approaches are more associated with interpretive and critical paradigms. However in practice it is often more complicated than that. Interviews may be structured and analysed in a quantitative manner, such as when numerical data is collected or when non-numerical answers are coded. Similarly, surveys may allow for open-ended responses and lead to in-depth study of individual cases.

In this writing we will look at some of those ‘epistemological’ and ‘technical’ arguments. We will analyse the arguments both for and against combining qualitative and quantitative research methods and assess the challenges in combining qualitative and quantitative methods. We will also explore some of the interesting features and characteristics of both qualitative and quantitative methods and will define mixed-method research and explain why it is significant for social researchers. Finally we will explore at the issues of research design in mixed methods, and evaluate the role of the ‘research question’ in helping researchers to determine how to conduct their research.

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To understand mixed methods research it may be helpful to define firstly what is meant by qualitative and quantitative research for it is mixing the best of both of these methodologies which makes mixed methods research increasingly popular. While the exact constitution of the two methodologies varies somewhat from author to author or is defined with varying degrees of specificity, there is substantial agreement about the fundamental antinomies and their practical implications for the conduct of research.In general, quantitative methods result in numeric information, which can be analysed through statistical testing. Quantitative research is conclusive in its nature as it tries to quantify the problem and understand how prevalent it is by looking for results which can be related to the larger population. Quantitative research has many strengths. It has the ability to produce true statements around mere thoughts or beliefs, through the use of controlled experiment and statistical techniques which allows for sophisticated analyses.

Control is of upmost importance in quantitative research because it enables the researcher to identify the causes of his or her observations. Experiments are conducted in an attempt to answer certain questions. Research attempts to identify why something happens, what causes something, or under what conditions does something occur. Control is necessary to avoid unambiguity. To answer questions in social science, elimination of the influence of variables is key to isolate the cause of an effect. Controlled inquiry is absolutely essential because without it the cause of the effect cannot be isolated. Control is closely followed by the requirement to be replicable or reliable. The data obtained in any research must be reliable; that is, the same result must be found if the study is repeated. If observations are not repeatable, explanations will be said to be unreliable.

Quantitative research also has its limitations. With this type of research because of human complexity it is difficult to rule out or control the many variables which occur. By nature the systematic philosophy tends to exclude notions of freedom, choice and moral responsibility and it can fail to take into account people’s unique ability to interpret their experiences, construct their own meanings and act on these. Lastly despite seeming so quantitative research methods are not totally objective because the researcher is subjectively involved in the very choice of a problem as worthy of investigation and in the interpretation of the results found.

Qualitative research in contrast is by definition exploratory, and used to define a problem or develop an approach to a problem. It is used to explore issues of interest and distinctions related to a problem. Common data collection methods used in qualitative research include focus groups, interviews and observation. A key characteristic of qualitative research is that an event can be understood adequately only if they are observed in context. Therefore, qualitative researchers must immerse themselves in the setting. A key quality of qualitative research is that the contexts of inquiry are not contrived; nothing is predefined or taken for granted. Qualitative researchers want those studied to speak for themselves, and give their opinion in their own words. Therefore, qualitative research is an interactive process. Ely et al add the following from Sherman and Webb (1988) to their definition, “qualitative implies a direct concern with experience as it is `lived’ or `felt’ or `undergone’ … Qualitative research, then, has the aim of understanding experience as nearly as possible as its participants feel it or live it. Qualitative research also has its strengths. Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed by more scientific or positivistic research. Because qualitative research uses a more descriptive style, it can be of particular benefit to researchers in order to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insights. Qualitative methods focus on generally smaller samples and tend to employ purposive sampling strategies. In contrast, Quantitative methods tend to employ probability sampling in order to maximize power and meet the assumptions of particular analytic strategies. Research planning benefits from understanding both purposive and probability sampling and how they compare in terms of generalizability, case selection, and focus of information, timing, rigidity of sampling frame, and the types of data generated. Nested designs or qualitative samples as a subset of larger quantitative samples can be implemented within larger studies when resources are limited and mixed methods are desirable. These designs provide for satisfactory levels of within subject analysis of both Qualitative and Quantitative data (Yoshikawa, Weisner, Kalil, & Way, 2008). Essential to the success of a nested design study is how the researcher selects the subset of participants for the more intensive.

The problem of validity or reliability crops up as a criticism of qualitative research. Because of the subjective nature of qualitative data it can be difficult to apply conventional standards of reliability and validity. In some instances contexts, situations, events, condition etc. such as researcher presence and opinion, has a profound effect on the subjects of study, may not be replicated nor can generalisations be made to a wider context with any confidence. And lastly of course qualitative research methods require great time and effort for data collection, analysis and interpretation.

Other challenges to integrating approaches stem from a number of practical design and logistical issues such as balancing the relative strengths of each, finding ways to bring relatively incompatible data closer without sacrificing quality, and developing strategies to dynamically integrate these data for efficient and cross-discipline analysis (Yoshikawa, Weisner, Kalil, & Way, 2008).

Bearing all this in mind and so if one believes both quantitative and qualitative have their limitations then possibly by combining both methods more concrete results can be attained. Ideally, we should strive to use both qualitative and quantitative research since they provide different perspectives and usually complement each other. This approach is a cost-effective alternative to the combination of in-person focus groups and a separate quantitative study. Mixed method is becoming increasingly popular as a research approach as it is a method that can combine what is good about both the qualitative and quantitative approaches.

Mixed methods research can serve a variety of purposes. Greene, Caracelli, and Graham (1989) point out that “researchers typically will use mixed design strategies which include triangulation, development, initiation, and expansion”. One can select and match the design strategy of their research to help understand better a specific issue or problem. This may mean that the researcher receives an understanding of social phenomenon or behaviour as well as the reasons that have influenced the behaviours. The phenomenon can then be numerically measured if required perhaps to determine if priority should be given to one or the other form of qualitative or quantitative research.

1. The ‘epistemological’ arguments both for and against combining qualitative and quantitative methods;

The quantitative qualitative divide has become one which in large part derives from epistemological issues and questions of research technique are taken to be systematically related to these issues. Trow’s dictum that problems determine methods is essentially a reference to a technical rather than an epistemological issue. It suggests not only that one technique can never be inherently superior to its supposed alternatives, but also that a technique is likely to be more useful in some contexts than others. Others, like Zelditch have sought to systematise such considerations by delineating the linkages between objects and techniques.

Such arguments are ‘technical’ in that they simply seek to demarcate those substantive issues or domains in which particular methods of investigation are appropriate or inappropriate. There is a myriad of technical reasons why participant observation is preferable to social surveys in such a sense or vice versa.

Traditionally, quantitative and qualitative research methods have had separate and distinct philosophical underpinnings and beliefs concerning the research approaches that are used to generate it. In line with this, one might argue that the use of mixed methods research designs raises questions concerning research philosophy, and also that there exists, a need to consider characteristic contradictions. Epistemology has historically concerned itself with “what should be” rather than “what actually is,” and settled its enquiries by what should be rather than by empirical investigation. Empirical research, in contrast, is generally concerned with how things actually work rather how they should, and settled their questions empirically.

Epistemology seems to be regarded as quite a negative discipline, with set rules of engagement in order to accomplish the title of science. The sociology of science, an empirical descendant of epistemology, doesn’t try to decide what should and shouldn’t count as science, but rather tells what people who claim to be doing science actually do, and what people who win the right to use the term science can realistically get away with. (Latour 1987) A major question is how one might combine qualitative and quantitative approaches to social research. The literature in this area generally ends up suggesting a division in which qualitative research generates hypotheses and quantitative research tests them.

Researchers tend to go about combining these different kinds of data in different ways. Thomas Kuhn (1970) noted that scientists learn their trade not by following abstract procedural recipes, but rather by examining exemplars of work in their field commonly regarded as well done. The best way to see how data of these various kinds can be combined is to examine how they were combined in exemplary works.

The mixed methods design model most commonly used is the concurrent triangulation model (Creswell, 2009). In this approach, the researcher collects both qualitative and quantitative data concurrently. This approach is important because it allows the researcher to determine if there is a pattern evident in the data. Most researchers employ this model of gathering both quantitative and qualitative data and compare the two data sources (Creswell, 2009). Comparison information can provide the researcher with valuable information that can enrich the descriptive reporting of data. For example, a closed-end survey can be administered, and at the same time, the researcher could conduct an interview to gather additional details. This approach permits the researcher to collect two types of data at once. The provided data is well rounded and detailed.

1. The ‘technical’ arguments both for and against combining qualitative and quantitative methods;

The principal objection to mixed methods research is that it violates the belief that specific methods are inextricably linked to certain ontological and epistemological ideas, and that the data derived from each must therefore be interpreted in different ways and are not compatible. Other objections are around the possible statistical measurement limitations of qualitative data when it has been quantitized as quantitized qualitative data is very vulnerable to collinearity (Roberts, 2000). Researchers having to collect and analyse qualitative data may reduce their sample size for the design to be less time-consuming and doing so can affect statistical procedures like analyses of variance and t-tests. This is a serious challenge for this design as the researcher may not have enough statistical power to support their research (Driscoll et al., 2007). Although this can be avoided if the researcher decides not to conduct a mixed method design that involves quantitization.

In contrast to the technical arguments against combining the methods it is possible that the quantitative approach linked to the positivist paradigm and the qualitative approach linked to the interpretivist paradigm can be utilised in the same research to study different research questions or different aspects of the question. This approach relates to the view that no one truth exists and differences in findings from different kinds of data tell us as much as similarities. A good case can be made for combining qualitative and quantitative methods in order to conduct different levels of enquiry. What is happening at micro level can be better understood by examining what’s going on at macro level and vice versa.

The dialectical position is similar to the argument for complementarity of approaches, in that it examines distinct yet related questions, recognising different ontological and epistemological traditions. Jennifer Mason believes “such discrepancies should spur us on to look more closely at the data, think harder about the implications and, ideally, go on to generate new theory”. Researchers make collaborative use of methods, working with the creative tensions thus engendered (Tashakkori and Teddlie, 2003, Mason 2006).

4. Challenges in combining qualitative and quantitative methods;

Mixed methods research should not be considered inherently valid (Bazeley, 2004); instead, trustworthiness and credibility must be applied through the use of guidelines, rules and procedures and attention to quality criteria. Quality criteria have been a concern for proponents of mixed methods research for some time. Onwuegbuzie and Johnson (2006) argue that validity issues faced by mixed methods researchers include representation, legitimation, and integration. Representation is the difficulty of explaining real life experience through text or numbers; legitimation refers to the trustworthiness of conclusions; and integration of these into the many threats that result from combining methods. This can leads to problems in producing high-quality mixed methods research, more simply put some mixed methods studies are fundamentally flawed from the outset because they combine and multiply the threats to validity and trustworthiness that comes with the different methods that they are combining.

Morse (2005), while embracing mixed methods, admitted to feeling a sense of “heresy” because the mixed methods had brought to the fore unanswered questions about mixing qualitative and quantitative approaches within a single set (p. 583). Bazeley (2004) warned about the dangers of mixed methods and the paradigmatic and methodological issues that it raised. Giddings and Grant (2007) considered mixed methods research simply as a bastardisation of positivism. Giddings (2006) warned “clothed in a semblance of inclusiveness, mixed methods could serve as a cover for the continuing hegemony of positivism, and maintain the marginalisation of non-positivist research methodologies”.

For example, practitioners may consider designing their studies in such a way that recognizes in advance the implications of the different time lines and rhythms of quantitative and qualitative investigations. In this way, it may be possible to build in greater opportunity to bring the two sets of findings together and for the quantitative and qualitative components of projects not to drift apart in terms of the phasing of the various stages of the overall research process.

A significant difficulty of mixed methods is that of merging analyses of quantitative and qualitative data to provide an integrated analysis. One consideration that may aid the linking of analyses is not to lose sight of the rationale for conducting mixed methods research in the first place.

Content analyses suggest that it is quite common for mixed methods researchers to neglect their rationales for doing such research and for it to be used in ways that differ from the rationales (Bryman, 2006a; Greene et al., 1989). In such circumstances, it is possibly unsurprising that mixed methods researchers experience uncertainty about how best to approach the potential connections between their quantitative and qualitative data. If mixed methods researchers return to their grounds for conducting such research in the first place, they may be able to use their arguments as a platform for conducting an analysis that is integrative.

The considerations of these issues also draws attention to a significant deficiency in our understanding of mixed methods practice, namely, insufficient attention has been paid to the fact that mixed methods research has to be written up. There is a general appreciation of issues such as the different ways in which quantitative and qualitative research methods might be combined and typologies of mixed methods research have identified the significance of such issues as priority and sequencing (e.g. Morgan, 1998). By contrast, the matter of how to present mixed methods findings in such a way that the quantitative and the qualitative findings are genuinely integrated, rather than standing as separate spheres or barely referring to each other, has not been touched upon to any significant extent in the burgeoning literature in this field. In genuinely integrated studies, the quantitative and the qualitative findings will be mutually informative. They will talk to each other, much like a conversation or debate, and the idea is then to construct a negotiated account of what they mean together. The metaphor of triangulation has sometimes hindered this process by concentrating on the degree to which findings are mutually reinforcing or irreconcilable. Mixed methods research is not necessarily just an exercise in testing findings against each other. Instead, it is about forging an overall or negotiated account of the findings that brings together both components of the conversation or debate.

Perhaps there may be some validity to these fears. Poor quality research, being sold as mixed methods, can violate the basics of both qualitative and quantitative methodologies (Morse, 2005). Giddings and Grant (2007), observed that in many instances, what was actually mixed were methods rather than methodologies, with the qualitative component too often in the subservient role.

Niglas (2009) alluded to the perpetrators being novice researchers in an emerging field, capturing but not fully comprehending the essence of the third paradigm. Perhaps the two issues most often ignored by novice researchers when planning and implementing mixed methods research are the adoption of an explicit philosophical stance and a design framework for organizing the inquiry. When one uses this design and when they quantify qualitative data it loses its flexibility and depth, which is one of the main advantages of qualitative research. This occurs because qualitative codes are multidimensional (Bazeley, 2004) while quantitative codes are one-dimensional and fixed so basically changing rich qualitative data to dichotomous variables produces one dimensional immutable data (Driscoll et al., 2007). It is possible for a researcher to avoid quantitizing qualitative data but it can become very time-consuming and complex process as it requires analysing, coding and integrating data from unstructured to structured data (Driscoll et al., 2007).

Mixed method design can be effective design to use but only if the researcher is well versed in both quantitative and qualitative research methods and also knows how to avoid the major challenges of the design.

Quantitative methods result in numeric information, which can be analysed through statistical testing. It is conclusive in its nature as it tries to quantify the problem and understand how prevalent it is by looking for results which can be related to the larger population. Qualitative research in contrast is by definition exploratory, and used to define a problem or develop an approach to a problem. It is used to explore issues of interest and distinctions related to a problem.

Quantitative research has the ability to produce true statements around mere thoughts or beliefs, through the use of controlled experiment and statistical techniques which allows for sophisticated analyses. Qualitative research because of close researcher involvement gains an insider’s view of the field which allows the researcher to find issues that are often missed by more scientific or positivistic research. With quantitative research because of human complexity it is difficult to rule out or control the many variables which occur. By nature the systematic philosophy tends to exclude notions of freedom, choice and moral responsibility and it can fail to take into account people’s unique ability to interpret their experiences, construct their own meanings and act on these. With quantitative research because of human complexity it is difficult to rule out or control the many variables which occur.

If one believes both quantitative and qualitative have their limitations then possibly by combining both methods more concrete results can be attained. Ideally, we should strive to use both qualitative and quantitative research since they provide different perspectives and usually complement each other. One can select and match the design strategy of their research to help understand better a specific issue or problem. Traditionally, quantitative and qualitative research methods have had separate and distinct philosophical underpinnings and beliefs concerning the research approaches that are used to generate it one might argue that the use of mixed methods research designs raises questions concerning research philosophy,

This paper has distinguished between technical and epistemological levels of discussion in the literature dealing with the quantitative qualitative distinction. ‘I’hree areas have been pinpointed in which the levels of discussion become unclear, fundamentally because the writers concerned often shuttle uneasily between epistemological and technical spheres of discourse.

A major question is how one might combine qualitative and quantitative approaches to social research. The principal objection to mixed methods research is that it violates the belief that specific methods are inextricably linked to certain ontological and epistemological ideas, and that the data derived from each must therefore be interpreted in different ways and are not compatible.

Mixed methods research should not be considered inherently valid (Bazeley, 2004); instead, trustworthiness and credibility must be applied through the use of guidelines, rules and procedures and attention to quality criteria. In contrast to the technical arguments against combining the methods it is possible that the quantitative approach linked to the positivist paradigm and the qualitative approach linked to the interpretivist paradigm can be utilised in the same research to study different research questions or different aspects of the question. This approach relates to the view that no one truth exists and differences in findings from different kinds of data tell us as much as similarities. The dialectical position is similar to the argument for complementarity of approaches, in that it examines distinct yet related questions, recognising different ontological and epistemological traditions.

Perhaps the two issues most often ignored by novice researchers when planning and implementing mixed methods research are the adoption of an explicit philosophical stance and a design framework for organizing the inquiry.

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