Quantitative and Qualitative Methods

Research Methods

Quantitative and qualitative research methods are the primary methods used in research. Each method has its strenghts and weaknesses. Mixed methods approaches combine both methods so that the weaknesses of one method are acompensated by the strengths of another. Figure 1 below shows the research strategies associated with each method.

Figure 1
research methods
Source: M. Duarte

Quantitative Methods

There are four main types of quantitative research designs: descriptive, correlational, quasi-experimental and experimental. The differences between the four types primarily relates to the degree the researcher designs for control of the variables in the experiment. Following is a brief description of each type of quantitative research design, as well as chart comparing and contrasting the approaches. Descriptive Design: seeks to describe the current status of a variable or phenomenon. The researcher does not begin with a hypothesis, but typically develops one after the data is collected. Data collection is mostly observational in nature. Correlational Design: explores the relationship between variables using statistical analyses. However, it does not look for cause and effect and therefore, is also mostly observational in terms of data collection.

Quasi-Experimental Design - (often referred to as Causal-Comparative) seeks to establish a cause-effect relationship between two or more variables. The researcher does not assign groups and does not manipulate the independent variable. Control groups are identified and exposed to the variable. Results are compared with results from groups not exposed to the variable. Experimental Designs: often called true experimentation, use the scientific method to establish cause-effect relationship among a group of variables in a research study. Researchers make an effort to control for all variables except the one being manipulated (the independent variable). The effects of the independent variable on the dependent variable are collected and analyzed for a relationship.

Sources:

Survey Methods– this involves either mail or web based surveys. The purpose of the survey is to produce statistics either quantitative or numeric about some aspects of a study population. The data is collected by asking people questions. Their answers constitutes the data to be analyzed numerically. Information is typically collected from a sample of the population versus the entire population.

Laboratory Experiments – Laboratory experiments take place in controlled environments and are the main method used in the natural sciences. The logic of the experimental method is that it is a controlled environment which enables the scientist to measure precisely the effects of independent variables on dependent variables, thus establishing cause and effect relationships. This in turn enables them to make predictions about how the dependent variable will act in the future. For a general introduction to the key features of experiments and the experimental method (including key terms such as hypothesis and dependent and independent variables) and some of their advantages please see this post: experiments in sociology: an introduction. The laboratory experiment and is commonly used psychology, however, they are less common in sociology.

Source: revisesociology.com

Numerical Methods – using numerical analysis, calculations, formulae or algorithms to analyze data. Most mathematical models used in the natural sciences are based on ordinary differential equations, partial differential equations, and integral equations.

Qualitative Methods

Ethnography - is a form of qualitative research and isdesigned to study cultures and groups. Ethnography methods include the observation of people in their natural setting for an extended period of time and in-depth interviews to clarify observations. Ethnography is the study of social interactions, behaviours, and perceptions that occur within groups, teams, organisations, and communities. Its roots can be traced back to anthropological studies of small, rural (and often remote) societies that were undertaken in the early 1900s, when researchers such as Bronislaw Malinowski and Alfred Radcliffe-Brown participated in these societies over long periods and documented their social arrangements and belief systems. The central aim of ethnography is to provide rich, holistic insights into people’s views and actions, as well as the nature (that is, sights, sounds) of the location they inhabit, through the collection of detailed observations and interviews. The task [of ethnographers] is to document the culture, the perspectives and practices, of the people in these settings. The aim is to ‘get inside’ the way each group of people sees the world.

The key features of ethnographic research are:

A strong emphasis on exploring the nature of a particular social phenomenon, rather than setting out to test hypotheses about it.
A tendency to work primarily with “unstructured data” —that is, data that have not been coded at the point of data collection as a closed set of analytical categories
Investigation of a small number of cases.

Source: revisesociology.com , bmj.com

Case Studies - this methodology is well established in the Social Sciences. This approach may help to inform practice by illustrating what has worked well, what has been achieved and what have been the issues or dilemmas. It is a type of research inquiry that examines a real life contemporary phenomenon. It is usual for multiple sources of evidence to be used. Single case studies have been frequently criticized because they are incapable of providing generalizing conclusions. Hamel et al. Yin argues that the relative size of the sample used, however small or large, does not transform a single or multiple case into a macroscopic study. The single case could be considered acceptable, provided it meets established objectives for the study. Outcomes from individual case studies are not statistically generalizable but analytically generalizable (Welsh and Lyons 2001).

Further reading:

David M (2006) Case study research. London: Sage
Dunbar G L (2005) Evaluating research methods in psychology: a case study approach. Oxford: BPS Blackwell
Gerring J (2007) Case study research: principles and practices. Cambridge: Cambridge University Press
Yin R K (2003) Applications of case study research. 2nd ed. London: Sage

Source: nottingham.ac.uk

Grounded Theory - is a systematic methodology in the social sciences involving the construction of theories through methodical gathering and analysis of data. Grounded theory is a research methodology which operates inductively, in contrast to the hypothetico-deductive approach. A study using grounded theory is likely to begin with a question, or even just with the collection of qualitative data. As researchers review the data collected, repeated ideas, concepts or elements become apparent, and are tagged with codes, which have been extracted from the data. As more data is collected, and re-reviewed, codes can be grouped into concepts, and then into categories. These categories may become the basis for new theory. Thus, grounded theory is quite different from the traditional model of research, where the researcher chooses an existing theoretical framework, and only then collects data to show how the theory does or does not apply to the phenomenon under study. Grounded theory involves the simultaneous collection and analysis of data, usually through observations. This approach develops the theory from the data collected rather than trying to test whether the collected data fits any preconceived theory. The researcher reads the text or data collected to identify theoretical and analytical codes. A central part of this exercise is constant comparison, or checking to see if the new data remains consistent with previously collected data. One approach to grounded theory is line by line coding, where the researcher codes each line of the data collected instantly, such as accepts what the interviewee says point blank without the chance of being influenced by preconceived notions that may creep up if the analysis is left for a later stage.

Source: wikipedia.org , brighthubpm.com

Action Research - Action research involves actively participating in a change situation, often via an existing organization, while simultaneously conducting research. Action research can also be undertaken by larger organizations or institutions, assisted or guided by professional researchers, with the aim of improving their strategies, practices and knowledge of the environments within which they practice. As designers and stakeholders, researchers work with others to propose a new course of action to help their community improve its work practices. Depending upon the nature of the people involved in the action research as well as the person(s) organizing it, there are different ways of describing action research:

Collaborative Action Research
Participatory Action Research
Community-Based Action Research
Youth Action Research
Action Research and Action Learning
Participatory Action Learning and Action Research
Collective Action Research
Action Science
Living Theory Action Research

Source: wikipedia.org

Phenomenological Studies - is a qualitative research method that is used to describe how human beings experience a certain phenomenon. A phenomenological study attempts to set aside biases and preconceived assumptions about human experiences, feelings, and responses to a particular situation. It allows the researcher to delve into the perceptions, perspectives, understandings, and feelings of those people who have actually experienced or lived the phenomenon or situation of interest. Therefore, phenomenology can be defined as the direct investigation and description of phenomena as consciously experienced by people living those experiences. Phenomenological research is typically conducted through the use of in-depth interviews of small samples of participants. By studying the perspectives of multiple participants, a researcher can begin to make generalizations regarding what it is like to experience a certain phenomenon from the perspective of those that have lived the experience.

The main characteristics of a phenomenology research:

It seeks to understand how people experience a particular situation or phenomenon.
It is conducted primarily through in-depth conversations and interviews; however, some studies may collect data from diaries, drawings, or observation.
Small samples sizes, often 10 or less participants, are common in phenomenological studies.
Interview questions are open-ended to allow the participants to fully describe the experience from their own view point.
Phenomenology is centered on the participants’ experiences with no regard to social or cultural norms, traditions, or preconceived ideas about the experience.
It focuses on these four aspects of a lived experience: lived spaced, lived body, lived time, and lived human relations.
Data collected is qualitative and analysis includes an attempt to identify themes or make generalizations regarding how a particular phenomenon is actually perceived or experienced.

Source: cirt.gcu.edu

Content Analysis - is a research technique used to make replicable and valid inferences by interpreting and coding textual material. By systematically evaluating texts (e.g., documents, oral communication, and graphics), qualitative data can be converted into quantitative data. Although the method has been used frequently in the social sciences, only recently has it become more prevalent among organizational scholars. It is promising for rigorous exploration of many important but difficult-to-study issues of interest to organizational researchers in areas as diverse as business policy and strategy, managerial and organizational cognition, organizational behavior, human resources, social-issues management, technology and innovation management, international management, and organizational theory.

Although content analysis is increasingly used by management researchers as a tool to analyze text and qualitative data, many researchers are unfamiliar with the various content analysis techniques and how to deal with challenges inherent in its application. These challenges include finding adequate measures, developing proxy dictionaries and coding schemes, working with texts from various sources, ensuring reliability and validity, and conducting manual versus computer-aided content analysis.

Source: terry.uga.edu

Data Analysis Methods

Typology - A way of describing groups of respondents displaying different clusters of behaviors, attitudes or views of the world. A typology generally consist of a set of descriptive names or "types", attached to thumbnail sketches of typical behavior and/or attitudes for each group. Typologies might be based on some specific behavior or on response to the client's brand. But they can go much further, claiming to categorize far broader attitudes and lifestyles. Typologies have been very popular and very useful in market research, but they rely on the assumption that individuals have stable attitudes, consumption patterns and a stable identity, assumptions that are now increasingly questioned.

Source: aqr.org.uk

Hermeneutics - Modern hermeneutics includes both verbal and non-verbal communication as well as semiotics, presuppositions, and pre-understandings. Hermeneutics has been broadly applied in the humanities, especially in law, history and theology. Hermeneutics was initially applied to the interpretation and has been later broadened to questions of general interpretation. The terms hermeneutics and exegesis are sometimes used interchangeably. Hermeneutics is a wider discipline which includes written, verbal, and non-verbal communication. Exegesis focuses primarily upon the word and grammar of texts. The value of hermeneutics as a credible, rigorous, and creative strategy to address aspects of professional practice that similarly need to be flexible, adaptable to particular needs, and justifiable in the contexts of evidence-based as well as client-centred practice.

Hermeneutic research enables you to make interpretations and gain an in-depth understanding of the researched phenomenon. Hermeneutic research emphasizes subjective interpretations in the research of meanings of texts, art, culture, social phenomena and thinking. Thus, the strategy forms an opposite to those research strategies which stress objectivity and independence from interpretations in the formation of knowledge. You can use a variety of approaches and methods of analysis, as well as discipline-specific methods, to interpret phenomena but you need to bear in mind that hermeneutic research is a qualitative research strategy.

Source: semanticscholar.org , koppa.jyu.fi

Matrix Analysis - is a complementary analytic strategy in qualitative inquiry. A research matrix is a tool to help organize the information for further analysis.

Analytic Induction - Analytic induction (AI) is a research logic used to collect data, develop analysis, and organize the presentation of research findings. Its formal objective is causal explanation, a specification of the individually necessary and jointly sufficient conditions for the emergence of some part of social life. AI calls for the progressive redefinition of the phenomenon to be explained (the explanandum) and of explanatory factors (the explanans), such that a perfect (sometimes called “universal”) relationship is maintained. Initial cases are inspected to locate common factors and provisional explanations. As new cases are examined and initial hypotheses are contradicted, the explanation is reworked in one or both of two ways. The definition of the explanandum may be redefined so that troublesome cases either become consistent with the explanans or are placed outside the scope of the inquiry; or the explanans may be revised so that all cases of the target phenomenon display the explanatory conditions. There is no 2 methodological value in piling up confirming cases; the strategy is exclusively qualitative, seeking encounters with new varieties of data in order to force revisions that will make the analysis valid when applied to an increasingly diverse range of cases. The investigation continues until the researcher can no longer practically pursue negative cases.

Source: sciencedirect.com , sscnet.ucla.edu

Constant Comparison (GT) – The goal of the Grounded Theory approach is to generate theories that explain how some aspect of the social world works. The goal is to develop a theory that emerges from and is therefore connected to the reality the theory is developed to explain. The contant comparative method is a method for analyzing data in order to develop a grounded theory. Glaser and Strauss (1967) suggest that when used to generate theory, the comparative analytical method they describe can be applied to social units of any size. The constant comparative method is used by the researcher to develop concepts from the data by coding and analyzing at the same time. The constant comparative method “combines systematic data collection, coding, and analysis with theoretical sampling in order to generate theory that is integrated, close to the data, and expressed in a form clear enough for further testing”. Constant comparative methodology incorporates four stages: “(1) comparing incidents applicable to each category, (2) integrating categories and their properties, (3) delimiting the theory, and (4) writing the theory”. Throughout the four stages of the constant comparative method, the researcher continually sorts through the data collection, analyzes and codes the information, and reinforces theory generation through the process of theoretical sampling. The benefit of using this method is that the research begins with raw data; through constant comparisons a substantive theory will emerge. Grounded theory is a labor-intensive task that requires the researcher to invest time in the processes of analysis and data collection.

Source: semanticscholar.org , qualres.org

Content Analysis - Content analysis is a research technique used to make replicable and valid inferences by interpreting and coding textual material. By systematically evaluating texts (e.g., documents, oral communication, and graphics), qualitative data can be converted into quantitative data. Although the method has been used frequently in the social sciences, only recently has it become more prevalent among organizational scholars.

Content analysis is valuable in organizational research because it allows researchers to recover and examine the nuances of organizational behaviors, stakeholder perceptions, and societal trends. It is also an important bridge between purely quantitative and purely qualitative research methods. In one regard, content analysis allows researchers to analyze socio-cognitive and perceptual constructs that are difficult to study via traditional quantitative archival methods. At the same time, it allows researchers to gather large samples that may be difficult to employ in purely qualitative studies.

Source: terry.uga.edu , sciencedirect.com

Taxonomy - Taxonomy is a formal system for classifying multifaceted, complex phenomena according to a set of common conceptual domains and dimensions in qualitative analysis. Taxonomies promote increased clarity in defining and hence comparing diverse, complex interventions, which are common in health policy and management. Themes are recurrent unifying concepts or statements about the subject of inquiry. Themes are fundamental concepts that characterize specific experiences of individual participants by the more general insights that are apparent from the whole of the data.

Source: ncbi.nlm.nih.gov

Framework / Thematic Analysis - The Framework Method is becoming an increasingly popular approach to the management and analysis of qualitative data in health research. However, there is confusion about its potential application and limitations. Used effectively, with the leadership of an experienced qualitative researcher, the Framework Method is a systematic and flexible approach to analyzing qualitative data and is appropriate for use in research teams even where not all members have previous experience of conducting qualitative research.

The Framework Method for the management and analysis of qualitative data has been used since the 1980s. The method originated in large-scale social policy research but is becoming an increasingly popular approach in medical and health research; however, there is some confusion about its potential application and limitations. The Framework Method sits within a broad family of analysis methods often termed thematic analysis or qualitative content analysis. These approaches identify commonalities and differences in qualitative data, before focusing on relationships between different parts of the data, thereby seeking to draw descriptive and/or explanatory conclusions clustered around themes.

The Framework Method was developed by researchers, Jane Ritchie and Liz Spencer, from the Qualitative Research Unit at the National Centre for Social Research in the United Kingdom in the late 1980s for use in large-scale policy research. It is now used widely in other areas, including health research. Its defining feature is the matrix output: rows (cases), columns (codes) and ‘cells’ of summarized data, providing a structure into which the researcher can systematically reduce the data, in order to analyze it by case and by code. Most often a ‘case’ is an individual interviewee, but this can be adapted to other units of analysis, such as predefined groups or organizations. While in-depth analyses of key themes can take place across the whole data set, the views of each research participant remain connected to other aspects of their account within the matrix so that the context of the individual’s views is not lost. Comparing and contrasting data is vital to qualitative analysis and the ability to compare with ease data across cases as well as within individual cases is built into the structure and process of the Framework Method.

The Framework Method provides clear steps to follow and produces highly structured outputs of summarized data. It is therefore useful where multiple researchers are working on a project, particularly in multi-disciplinary research teams were not all members have experience of qualitative data analysis, and for managing large data sets where obtaining a holistic, descriptive overview of the entire data set is desirable. However, caution is recommended before selecting the method as it is not a suitable tool for analyzing all types of qualitative data or for answering all qualitative research questions, nor is it an ‘easy’ version of qualitative research for quantitative researchers. Importantly, the Framework Method cannot accommodate highly heterogeneous data, i.e. data must cover similar topics or key issues so that it is possible to categorize it. Individual interviewees may, of course, have very different views or experiences in relation to each topic, which can then be compared and contrasted. The Framework Method is most commonly used for the thematic analysis of semi-structured interview transcripts.

Source: ncbi.nlm.nih.gov

Semiotics - Semiotics is a discipline, in which culture, society and natural phenomena are explored as signs. The fundamental question in semiotics is how meanings are formed. Semiotic research approaches signs as existing in various forms: pictures, words, letters, objects, natural objects, gestures, phenomena and actions. Semiotics explores the content of signs, their use and the formation of meanings of signs at both the level of a single sign and the broader systems and structures formed by signs. Semiotics as a discipline includes several distinguished traditions, each using its own terminology and concepts. If you use semiotic analysis (involving semiotic concepts and models) your aims are to analyze, understand and interpret signs, the meanings of signs, and the interaction of signs and sign systems. Semiotic analysis views the sign and use of signs as a part of a sign system. A sign system directs the use of the sign and thus, the system always has an effect on the contents of individual signs. A sign is never independent of the meanings and use of other signs. Semiotic analysis uses both qualitative and interpretative content analysis involving semiotic concepts and terms.

Source: koppa.jyu.fi

Narrative Analysis – Narrative research is a term that subsumes a group of approaches that in turn rely on the written or spoken words or visual representation of individuals. These approaches typically focus on the lives of individuals as told through their own stories. The emphasis in such approaches is on the story, typically both what and how is narrated. Narrative research can be considered both a research method in itself but also the phenomenon under study.

Narrative methods can be considered “real world measures” that are appropriate when “real life problems” are investigated. In a basic linear approach, they encompass the study of the experiences of a single individual embracing stories of the life and exploring the learned significance of those individual experiences. However, in most cases one will be creating an aggregate of narratives each bearing on the others. Narrative research is set out by the validation of the audience. It is a useful part of the social science investigation, but may not always stand alone for evidence and support for the conclusions of a report.

Source: clarku.edu , atlasti.com

Domain Analysis – Domain analysis helps researchers discover patterns in the descriptive detail of field notes; taxonomic analysis organizes elements in domains into cohesive structures, which are revealed through focused inquiries. Selective inquiries take another step by identifying contrasts and similarities among elements in the domains.

Source: academic.oup.com , qualitativeinquirydailylife.wordpress.com

Discourse Analysis - There are numerous approaches to qualitative research, and discourse analysis is one of them. The study of naturally occurring language in any social context is discourse analysis, and it makes use of various qualitative methods to increase our understanding of human experience. Discourse analysis is sometimes defined as the analysis of language 'beyond the sentence'. This contrasts with types of analysis more typical of modern linguistics, which are chiefly concerned with the study of grammar: the study of smaller bits of language, such as sounds (phonetics and phonology), parts of words (morphology), meaning (semantics), and the order of words in sentences (syntax). Discourse analysts study larger chunks of language as they flow together. Some discourse analysts consider the larger discourse context in order to understand how it affects the meaning of the sentence.

Source: linguisticsociety.org , researchgate.net

Heuristic Analysis/Phenomenology - Heuristic research using qualitative methods is based on a methodology which has been developed at the University of Hamburg and has been widely applied. Our methodology aims at discovery and uses the variables of research design in a certain way to serve this purpose. It suggests to the research person to follow four basic rules, which are specified below. It draws on a wide variety of methods including the "qualitative experiment". The concept of the research process involves seeing dialogue as a specific form of dialectic. An integrated part of the methodology is its verification procedure with tests of validity, reliability and range of findings. Qualitative heuristics are applicable to all topics within psychology and the human and social sciences which are open to empirical research. Qualitative data are especially suitable to discover qualitative relations such as structure or patterns and structural changes.

Source: qualitative-research.net , citeseerx.ist.psu.edu