Peter Lyons and Howard J. Doueck
- Published in print:
- 2009
- Published Online:
- February 2010
- ISBN:
- 9780195373912
- eISBN:
- 9780199865604
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195373912.001.0001
- Subject:
- Social Work, Research and Evaluation
This book is intended to be read at any stage in the dissertation process, but will be particularly useful in the early stages of preparation for a social work dissertation, and as a reference ...
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This book is intended to be read at any stage in the dissertation process, but will be particularly useful in the early stages of preparation for a social work dissertation, and as a reference resource throughout. The book is a guide to successful dissertation completion. Content includes a brief history and overview of social work doctoral education in the United States, the importance of values in social work, and the relationship between personal, research, and social work values. Chapter 2 addresses issues in selecting and working with the dissertation supervisor and committee, as well as the role and tasks of all three parties in successful completion of the dissertation. In Chapter 3 strategies for researching, and evaluating the literature, as well as writing the literature review are discussed. In addition, the relevance of theory to social work research is examined. Chapter 4 describes ethical issues in social research and requirements for the protection of human subjects. In addition, an overview of both quantitative and qualitative research methods is provided. In Chapter 5 sample design and sample size are discussed in relation to both quantitative and qualitative research. The significance of the psychometric properties of measurement instruments is also discussed. Chapter 6 addresses issues in data collection, data management, and data analysis in qualitative and quantitative research. Finally Chapter 7 presents strategies for dissertation writing including structure and content, as well as data presentation.Less
This book is intended to be read at any stage in the dissertation process, but will be particularly useful in the early stages of preparation for a social work dissertation, and as a reference resource throughout. The book is a guide to successful dissertation completion. Content includes a brief history and overview of social work doctoral education in the United States, the importance of values in social work, and the relationship between personal, research, and social work values. Chapter 2 addresses issues in selecting and working with the dissertation supervisor and committee, as well as the role and tasks of all three parties in successful completion of the dissertation. In Chapter 3 strategies for researching, and evaluating the literature, as well as writing the literature review are discussed. In addition, the relevance of theory to social work research is examined. Chapter 4 describes ethical issues in social research and requirements for the protection of human subjects. In addition, an overview of both quantitative and qualitative research methods is provided. In Chapter 5 sample design and sample size are discussed in relation to both quantitative and qualitative research. The significance of the psychometric properties of measurement instruments is also discussed. Chapter 6 addresses issues in data collection, data management, and data analysis in qualitative and quantitative research. Finally Chapter 7 presents strategies for dissertation writing including structure and content, as well as data presentation.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0001
- Subject:
- Sociology, Social Research and Statistics
This book investigates the relationship between the quantitative and qualitative research traditions in the social sciences, with a particular focus on political science and sociology. It argues that ...
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This book investigates the relationship between the quantitative and qualitative research traditions in the social sciences, with a particular focus on political science and sociology. It argues that the two traditions are alternative cultures with distinctive research procedures and practices, each having its own values, beliefs, and norms. The book considers the ways in which the traditions differ in terms of methodology, such as type of research question, mode of data analysis, and method of inference. It suggests that the two traditions draw on alternative mathematical foundations: quantitative research is grounded in inferential statistics (that is, probability and statistical theory), whereas qualitative research is (often implicitly) rooted in logic and set theory. This chapter discusses the book's approach to characterizing and comparing the two cultures of social science research and explains what is distinctive about qualitative research.Less
This book investigates the relationship between the quantitative and qualitative research traditions in the social sciences, with a particular focus on political science and sociology. It argues that the two traditions are alternative cultures with distinctive research procedures and practices, each having its own values, beliefs, and norms. The book considers the ways in which the traditions differ in terms of methodology, such as type of research question, mode of data analysis, and method of inference. It suggests that the two traditions draw on alternative mathematical foundations: quantitative research is grounded in inferential statistics (that is, probability and statistical theory), whereas qualitative research is (often implicitly) rooted in logic and set theory. This chapter discusses the book's approach to characterizing and comparing the two cultures of social science research and explains what is distinctive about qualitative research.
Peter Lyons and Howard J. Doueck
- Published in print:
- 2009
- Published Online:
- February 2010
- ISBN:
- 9780195373912
- eISBN:
- 9780199865604
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195373912.003.0004
- Subject:
- Social Work, Research and Evaluation
This chapter describes ethical issues in social research including discussion of the NASW Code of Ethics, Institutional Review Board (IRB) processes, and requirements for the protection of human ...
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This chapter describes ethical issues in social research including discussion of the NASW Code of Ethics, Institutional Review Board (IRB) processes, and requirements for the protection of human subjects. In addition, quantitative research methods; qualitative research methods; mixed-methods research designs; experimental, quasi-experimental, explanatory, exploratory, and descriptive research; program evaluation; and the relative merits of disparate models of research are also presented. The requirements of rigor in both quantitative and qualitative studies and evaluating the degree of fit between research strategies and problems under investigation are also discussed.Less
This chapter describes ethical issues in social research including discussion of the NASW Code of Ethics, Institutional Review Board (IRB) processes, and requirements for the protection of human subjects. In addition, quantitative research methods; qualitative research methods; mixed-methods research designs; experimental, quasi-experimental, explanatory, exploratory, and descriptive research; program evaluation; and the relative merits of disparate models of research are also presented. The requirements of rigor in both quantitative and qualitative studies and evaluating the degree of fit between research strategies and problems under investigation are also discussed.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0003
- Subject:
- Sociology, Social Research and Statistics
This chapter examines two approaches used in social science research: the “causes-of-effects” approach and the “effects-of-causes” approach. The quantitative and qualitative cultures differ in the ...
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This chapter examines two approaches used in social science research: the “causes-of-effects” approach and the “effects-of-causes” approach. The quantitative and qualitative cultures differ in the extent to which and the ways in which they address causes-of-effects and effects-of-causes questions. Quantitative scholars, who favor the effects-of-causes approach, focus on estimating the average effects of particular variables within populations or samples. By contrast, qualitative scholars employ individual case analysis to explain outcomes as well as the effects of particular causal factors. The chapter first considers the type of research question addressed by both quantitative and qualitative researchers before discussing the use of within-case analysis by the latter to investigate individual cases versus cross-case analysis by the former to elucidate central tendencies in populations. It also describes the complementarities between qualitative and quantitative research that make mixed-method research possible.Less
This chapter examines two approaches used in social science research: the “causes-of-effects” approach and the “effects-of-causes” approach. The quantitative and qualitative cultures differ in the extent to which and the ways in which they address causes-of-effects and effects-of-causes questions. Quantitative scholars, who favor the effects-of-causes approach, focus on estimating the average effects of particular variables within populations or samples. By contrast, qualitative scholars employ individual case analysis to explain outcomes as well as the effects of particular causal factors. The chapter first considers the type of research question addressed by both quantitative and qualitative researchers before discussing the use of within-case analysis by the latter to investigate individual cases versus cross-case analysis by the former to elucidate central tendencies in populations. It also describes the complementarities between qualitative and quantitative research that make mixed-method research possible.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0017
- Subject:
- Sociology, Social Research and Statistics
This book concludes by reemphasizing important differences in the nature of qualitative and quantitative research—differences that extend across research design, data analysis, and causal inference. ...
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This book concludes by reemphasizing important differences in the nature of qualitative and quantitative research—differences that extend across research design, data analysis, and causal inference. While their differences are considerable, the book argues that both research cultures can complement one another in terms of explaining the social and political world. However, a fruitful collaboration between quantitative and qualitative research—one built around mutual respect and appreciation—is possible only if scholars of both traditions understand and acknowledge their differences. These differences, summarized in tables, come in the areas of individual cases, causality and causal models, populations and data, concepts and measurement, and asymmetry. The book also contends that mixing the qualitative and quantitative cultures will contribute to methodological pluralism in the social sciences.Less
This book concludes by reemphasizing important differences in the nature of qualitative and quantitative research—differences that extend across research design, data analysis, and causal inference. While their differences are considerable, the book argues that both research cultures can complement one another in terms of explaining the social and political world. However, a fruitful collaboration between quantitative and qualitative research—one built around mutual respect and appreciation—is possible only if scholars of both traditions understand and acknowledge their differences. These differences, summarized in tables, come in the areas of individual cases, causality and causal models, populations and data, concepts and measurement, and asymmetry. The book also contends that mixing the qualitative and quantitative cultures will contribute to methodological pluralism in the social sciences.
Denise E. Bronson and Tamara S. Davis
- Published in print:
- 2011
- Published Online:
- January 2012
- ISBN:
- 9780195337365
- eISBN:
- 9780199918201
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195337365.001.0001
- Subject:
- Social Work, Research and Evaluation
Evidence-based practice (EBP) promises to have a profound impact on social work practice, education, and scholarship, but adopting EBP depends on the availability of evidence to support this ...
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Evidence-based practice (EBP) promises to have a profound impact on social work practice, education, and scholarship, but adopting EBP depends on the availability of evidence to support this endeavour and on strategies to synthesize this information. Systematic reviews provide a comprehensive, unbiased method for retrieving and synthesizing relevant research. Finding and Evaluating Evidence: Systematic Reviews and Evidence-based Practice is a concise introduction to systematic reviews that describes the steps required to complete a review and the criteria that can be used to assess the quality of existing reviews. This pocket guide provides straight-forward information on how to 1) define a search question that clearly defines the parameters of the problem, 2) develop a search strategy that is transparent and comprehensive to insure that all relevant research is included in the review, 3) assess the quality and credibility of existing research, and 4) summarize the available research to support EBP in social work. One of the distinguishing features of this book is that both quantitative and qualitative synthesis methods are presented, and examples are provided to illustrate the steps and decisions associated with each approach to research synthesis. This pocket guide is an excellent introduction to EBP and systematic reviews that will be valued by social work students, practitioners, and scholars.Less
Evidence-based practice (EBP) promises to have a profound impact on social work practice, education, and scholarship, but adopting EBP depends on the availability of evidence to support this endeavour and on strategies to synthesize this information. Systematic reviews provide a comprehensive, unbiased method for retrieving and synthesizing relevant research. Finding and Evaluating Evidence: Systematic Reviews and Evidence-based Practice is a concise introduction to systematic reviews that describes the steps required to complete a review and the criteria that can be used to assess the quality of existing reviews. This pocket guide provides straight-forward information on how to 1) define a search question that clearly defines the parameters of the problem, 2) develop a search strategy that is transparent and comprehensive to insure that all relevant research is included in the review, 3) assess the quality and credibility of existing research, and 4) summarize the available research to support EBP in social work. One of the distinguishing features of this book is that both quantitative and qualitative synthesis methods are presented, and examples are provided to illustrate the steps and decisions associated with each approach to research synthesis. This pocket guide is an excellent introduction to EBP and systematic reviews that will be valued by social work students, practitioners, and scholars.
Dale C. Copeland
- Published in print:
- 2014
- Published Online:
- October 2017
- ISBN:
- 9780691161587
- eISBN:
- 9781400852703
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691161587.003.0003
- Subject:
- Political Science, International Relations and Politics
This chapter explores the degree to which an expectations approach can help us make sense of the seemingly contradictory findings of the large-N quantitative research that has dominated the study of ...
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This chapter explores the degree to which an expectations approach can help us make sense of the seemingly contradictory findings of the large-N quantitative research that has dominated the study of interdependence and war over the last two decades. It also lays out a new approach to qualitative historical analysis for rare events research—one that minimizes the problems of selection bias and generalizability by covering the essential universe of cases for a chosen period of time. Additionally, the chapter discusses how qualitative research can help overcome the limitations of quantitative methods in the measuring of leader expectations about the future.Less
This chapter explores the degree to which an expectations approach can help us make sense of the seemingly contradictory findings of the large-N quantitative research that has dominated the study of interdependence and war over the last two decades. It also lays out a new approach to qualitative historical analysis for rare events research—one that minimizes the problems of selection bias and generalizability by covering the essential universe of cases for a chosen period of time. Additionally, the chapter discusses how qualitative research can help overcome the limitations of quantitative methods in the measuring of leader expectations about the future.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0007
- Subject:
- Sociology, Social Research and Statistics
This chapter examines how the qualitative and quantitative research traditions treat within-case analysis versus cross-case analysis for causal inference. In qualitative research, the primary focus ...
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This chapter examines how the qualitative and quantitative research traditions treat within-case analysis versus cross-case analysis for causal inference. In qualitative research, the primary focus is on specific events and processes taking place within each individual case. Leading qualitative methodologies of hypothesis testing, such as process tracing and counterfactual analysis, are fundamentally methods of within-case analysis. By contrast, quantitative research traditionally involves exclusively cross-case comparison. The chapter begins with a comparison of the typical roles (or nonroles) of within-case and cross-case analysis in case studies versus experiments. It then considers how causal inference in quantitative and qualitative research is linked to the use of “data-set observations” and “causal-process observations,” respectively. It also explains the differences between process-tracing tests and statistical tests and concludes by suggesting that cross-case analysis and within-case analysis can and often should be combined.Less
This chapter examines how the qualitative and quantitative research traditions treat within-case analysis versus cross-case analysis for causal inference. In qualitative research, the primary focus is on specific events and processes taking place within each individual case. Leading qualitative methodologies of hypothesis testing, such as process tracing and counterfactual analysis, are fundamentally methods of within-case analysis. By contrast, quantitative research traditionally involves exclusively cross-case comparison. The chapter begins with a comparison of the typical roles (or nonroles) of within-case and cross-case analysis in case studies versus experiments. It then considers how causal inference in quantitative and qualitative research is linked to the use of “data-set observations” and “causal-process observations,” respectively. It also explains the differences between process-tracing tests and statistical tests and concludes by suggesting that cross-case analysis and within-case analysis can and often should be combined.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0010
- Subject:
- Sociology, Social Research and Statistics
This chapter considers two fundamental differences between the quantitative and qualitative research traditions with respect to conceptualization and measurement: these differences are related to the ...
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This chapter considers two fundamental differences between the quantitative and qualitative research traditions with respect to conceptualization and measurement: these differences are related to the relative emphasis placed on definitions versus indicators in the two cultures. The first difference concerns the relative importance assigned to issues of concept definition versus issues of concept measurement. Qualitative researchers are centrally concerned with definitional issues and the meaning of their concepts, whereas their quantitative counterparts are more interested in the quantitative measurement of latent variables. The second difference concerns error and the coding of cases. The chapter examines how characteristics versus indicators are defined in the qualitative and quantitative research paradigms. It also discusses the relationship between “error,” which is central to all statistics, and “fuzziness,” which is important in qualitative research.Less
This chapter considers two fundamental differences between the quantitative and qualitative research traditions with respect to conceptualization and measurement: these differences are related to the relative emphasis placed on definitions versus indicators in the two cultures. The first difference concerns the relative importance assigned to issues of concept definition versus issues of concept measurement. Qualitative researchers are centrally concerned with definitional issues and the meaning of their concepts, whereas their quantitative counterparts are more interested in the quantitative measurement of latent variables. The second difference concerns error and the coding of cases. The chapter examines how characteristics versus indicators are defined in the qualitative and quantitative research paradigms. It also discusses the relationship between “error,” which is central to all statistics, and “fuzziness,” which is important in qualitative research.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- book
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.001.0001
- Subject:
- Sociology, Social Research and Statistics
Some in the social sciences argue that the same logic applies to both qualitative and quantitative research methods. This book demonstrates that these two paradigms constitute different cultures, ...
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Some in the social sciences argue that the same logic applies to both qualitative and quantitative research methods. This book demonstrates that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. The book identifies and discusses major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, the book also seeks to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. The book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.Less
Some in the social sciences argue that the same logic applies to both qualitative and quantitative research methods. This book demonstrates that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. The book identifies and discusses major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, the book also seeks to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. The book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0016
- Subject:
- Sociology, Social Research and Statistics
This chapter focuses on scope conditions in qualitative and quantitative research. It begins with a simple example, Hooke's law from physics, to illustrate the concept of “scope.” It then considers ...
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This chapter focuses on scope conditions in qualitative and quantitative research. It begins with a simple example, Hooke's law from physics, to illustrate the concept of “scope.” It then considers some of the most popular “within-model” responses to causal heterogeneity problems, showing that the option of changing the causal model to address causal heterogeneity issues is more attractive to quantitative researchers than to qualitative researchers. It also examines how the existence of causal complexity and concerns about fit with data can lead scholars to use scope conditions. Finally, it discusses the relationship between empirical testing and the proposed scope of theories and suggests that issues of scope raise Fundamental Tradeoffs in social science research, including tradeoffs concerning the tension between generality and parsimony, and between generality and issues of model fit.Less
This chapter focuses on scope conditions in qualitative and quantitative research. It begins with a simple example, Hooke's law from physics, to illustrate the concept of “scope.” It then considers some of the most popular “within-model” responses to causal heterogeneity problems, showing that the option of changing the causal model to address causal heterogeneity issues is more attractive to quantitative researchers than to qualitative researchers. It also examines how the existence of causal complexity and concerns about fit with data can lead scholars to use scope conditions. Finally, it discusses the relationship between empirical testing and the proposed scope of theories and suggests that issues of scope raise Fundamental Tradeoffs in social science research, including tradeoffs concerning the tension between generality and parsimony, and between generality and issues of model fit.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0002
- Subject:
- Sociology, Social Research and Statistics
This chapter considers some key ideas from logic and set theory as they relate to qualitative research in the social sciences, including ideas concerning necessary and sufficient conditions. It also ...
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This chapter considers some key ideas from logic and set theory as they relate to qualitative research in the social sciences, including ideas concerning necessary and sufficient conditions. It also highlights a major contrast between qualitative and quantitative research: whereas quantitative research draws on mathematical tools associated with statistics and probability theory, qualitative research is often based on set theory and logic. The chapter first compares the natural language of logic in the qualitative culture with the language of probability and statistics in the quantitative culture. It then considers the necessary conditions and sufficient conditions as basis for qualitative methods, focusing on set theory and Venn diagrams, two-by-two tables, and truth tables. It also discusses the use of qualitative and quantitative aggregation techniques and concludes by explaining the criteria for assessing the “fit” of the model or the “importance” of a given causal factor.Less
This chapter considers some key ideas from logic and set theory as they relate to qualitative research in the social sciences, including ideas concerning necessary and sufficient conditions. It also highlights a major contrast between qualitative and quantitative research: whereas quantitative research draws on mathematical tools associated with statistics and probability theory, qualitative research is often based on set theory and logic. The chapter first compares the natural language of logic in the qualitative culture with the language of probability and statistics in the quantitative culture. It then considers the necessary conditions and sufficient conditions as basis for qualitative methods, focusing on set theory and Venn diagrams, two-by-two tables, and truth tables. It also discusses the use of qualitative and quantitative aggregation techniques and concludes by explaining the criteria for assessing the “fit” of the model or the “importance” of a given causal factor.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0004
- Subject:
- Sociology, Social Research and Statistics
This chapter compares two causal models used in qualitative and quantitative research: an additive-linear model and a set-theoretic model. The additive-linear causal model is common in the ...
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This chapter compares two causal models used in qualitative and quantitative research: an additive-linear model and a set-theoretic model. The additive-linear causal model is common in the statistical culture, whereas the set-theoretic model is often used (implicitly) in the qualitative culture. After providing an overview of the two causal models, the chapter considers the main differences between them. It then gives an example to illustrate how a set-theoretic causal model is implicitly used in the within-case analysis of a specific outcome. It also explains how the form of causal complexity varies across the quantitative and qualitative paradigms. Finally, it examines another difference between the causal models used in quantitative and qualitative research, one that revolves around the concept of “equifinality” or “multiple causation.” The chapter suggests that while the two causal models are quite different, neither is a priori correct.Less
This chapter compares two causal models used in qualitative and quantitative research: an additive-linear model and a set-theoretic model. The additive-linear causal model is common in the statistical culture, whereas the set-theoretic model is often used (implicitly) in the qualitative culture. After providing an overview of the two causal models, the chapter considers the main differences between them. It then gives an example to illustrate how a set-theoretic causal model is implicitly used in the within-case analysis of a specific outcome. It also explains how the form of causal complexity varies across the quantitative and qualitative paradigms. Finally, it examines another difference between the causal models used in quantitative and qualitative research, one that revolves around the concept of “equifinality” or “multiple causation.” The chapter suggests that while the two causal models are quite different, neither is a priori correct.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0014
- Subject:
- Sociology, Social Research and Statistics
This chapter discusses quantitative and qualitative practices of case-study selection when the goal of the analysis is to evaluate causal hypotheses. More specifically, it considers how the different ...
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This chapter discusses quantitative and qualitative practices of case-study selection when the goal of the analysis is to evaluate causal hypotheses. More specifically, it considers how the different causal models used in the qualitative and quantitative research cultures shape the kind of cases that provide the most leverage for hypothesis testing. The chapter examines whether one should select cases based on their value on the dependent variable. It also evaluates the kinds of cases that provide the most leverage for causal inference when conducting case-study research. It shows that differences in research goals between quantitative and qualitative scholars yield distinct ideas about best strategies of case selection. Qualitative research places emphasis on explaining particular cases; quantitative research does not.Less
This chapter discusses quantitative and qualitative practices of case-study selection when the goal of the analysis is to evaluate causal hypotheses. More specifically, it considers how the different causal models used in the qualitative and quantitative research cultures shape the kind of cases that provide the most leverage for hypothesis testing. The chapter examines whether one should select cases based on their value on the dependent variable. It also evaluates the kinds of cases that provide the most leverage for causal inference when conducting case-study research. It shows that differences in research goals between quantitative and qualitative scholars yield distinct ideas about best strategies of case selection. Qualitative research places emphasis on explaining particular cases; quantitative research does not.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0008
- Subject:
- Sociology, Social Research and Statistics
This chapter examines how the qualitative and quantitative research traditions empirically assess theories about mechanisms when making causal inferences. In the qualitative paradigm, researchers ...
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This chapter examines how the qualitative and quantitative research traditions empirically assess theories about mechanisms when making causal inferences. In the qualitative paradigm, researchers carry out this assessment by attempting to observe causal mechanisms through process tracing and through the analysis of causal-process observations. In the qualitative paradigm, the within-case analysis of specific cases is combined with the effort to observe mechanisms. By contrast, statistical methods are not designed to observe mechanisms within particular cases. The chapter considers the importance of mechanisms in causal inference as well as the use of process tracing in multimethod vs. qualitative research. It shows that multimethod research, which integrates regression and case study analysis, is increasingly regarded as a best practice.Less
This chapter examines how the qualitative and quantitative research traditions empirically assess theories about mechanisms when making causal inferences. In the qualitative paradigm, researchers carry out this assessment by attempting to observe causal mechanisms through process tracing and through the analysis of causal-process observations. In the qualitative paradigm, the within-case analysis of specific cases is combined with the effort to observe mechanisms. By contrast, statistical methods are not designed to observe mechanisms within particular cases. The chapter considers the importance of mechanisms in causal inference as well as the use of process tracing in multimethod vs. qualitative research. It shows that multimethod research, which integrates regression and case study analysis, is increasingly regarded as a best practice.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0009
- Subject:
- Sociology, Social Research and Statistics
This chapter examines the use of counterfactual analysis in making causal inferences in the qualitative and quantitative research paradigms. To assess a counterfactual claim about a particular case, ...
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This chapter examines the use of counterfactual analysis in making causal inferences in the qualitative and quantitative research paradigms. To assess a counterfactual claim about a particular case, the typical approach is to conduct a within-case analysis of that case. Qualitative researchers formulate counterfactuals that are “conceivable,” in the sense that imagining that a cause had not occurred (or occurred differently) does not require fundamentally rewriting history. By contrast, quantitative scholars use counterfactuals mainly to illustrate a general causal model. The chapter first considers the Fundamental Problem of Causal Inference, which is the problem of a counterfactual, before discussing the statistical approach to counterfactuals. In particular, it describes the “minimum rewrite” rule. It suggests that counterfactual analyses are an important mode of causal inference within the qualitative tradition, but not commonly used within the quantitative tradition.Less
This chapter examines the use of counterfactual analysis in making causal inferences in the qualitative and quantitative research paradigms. To assess a counterfactual claim about a particular case, the typical approach is to conduct a within-case analysis of that case. Qualitative researchers formulate counterfactuals that are “conceivable,” in the sense that imagining that a cause had not occurred (or occurred differently) does not require fundamentally rewriting history. By contrast, quantitative scholars use counterfactuals mainly to illustrate a general causal model. The chapter first considers the Fundamental Problem of Causal Inference, which is the problem of a counterfactual, before discussing the statistical approach to counterfactuals. In particular, it describes the “minimum rewrite” rule. It suggests that counterfactual analyses are an important mode of causal inference within the qualitative tradition, but not commonly used within the quantitative tradition.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0011
- Subject:
- Sociology, Social Research and Statistics
This chapter examines how translation problems are manifested across the qualitative and quantitative cultures for issues related to concepts and measurement. In the quantitative research paradigm, ...
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This chapter examines how translation problems are manifested across the qualitative and quantitative cultures for issues related to concepts and measurement. In the quantitative research paradigm, one speaks of variables and indicators. X and Y are normally latent, unobserved variables for which one needs (quantitative) indicators. In practice, quantitative scholars might fuse the variable and the indicator into one entity. Qualitative researchers, on the other hand, tend to use the variable-indicator language which causes a translation problem and does not capture research practices in the qualitative culture. The chapter first considers the notion of “membership function,” which is important in the fuzzy-set approach to concepts, before discussing a fundamental principle of semantic transformations in the qualitative culture: the Principle of Unimportant Variation. It also explains the relationship between scale types and membership functions in fuzzy-set analysis.Less
This chapter examines how translation problems are manifested across the qualitative and quantitative cultures for issues related to concepts and measurement. In the quantitative research paradigm, one speaks of variables and indicators. X and Y are normally latent, unobserved variables for which one needs (quantitative) indicators. In practice, quantitative scholars might fuse the variable and the indicator into one entity. Qualitative researchers, on the other hand, tend to use the variable-indicator language which causes a translation problem and does not capture research practices in the qualitative culture. The chapter first considers the notion of “membership function,” which is important in the fuzzy-set approach to concepts, before discussing a fundamental principle of semantic transformations in the qualitative culture: the Principle of Unimportant Variation. It also explains the relationship between scale types and membership functions in fuzzy-set analysis.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0013
- Subject:
- Sociology, Social Research and Statistics
This chapter considers how opposing pairs of categories and typologies are used in the qualitative and quantitative research traditions. It begins with a discussion of the concepts of democracy and ...
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This chapter considers how opposing pairs of categories and typologies are used in the qualitative and quantitative research traditions. It begins with a discussion of the concepts of democracy and authoritarianism to illustrate the symmetric versus asymmetric approaches to conceptual opposites. In particular, it explains the Principle of Conceptual Opposites in qualitative research, which states that the meaning and measurement of a concept and its opposite are not symmetric. It then examines overlapping versus exclusive typologies, focusing on the Principle of Conceptual Overlap. It also describes the importance of semantics when dealing with cases that do not fit available categories if the goal is to have useful nominal categories.Less
This chapter considers how opposing pairs of categories and typologies are used in the qualitative and quantitative research traditions. It begins with a discussion of the concepts of democracy and authoritarianism to illustrate the symmetric versus asymmetric approaches to conceptual opposites. In particular, it explains the Principle of Conceptual Opposites in qualitative research, which states that the meaning and measurement of a concept and its opposite are not symmetric. It then examines overlapping versus exclusive typologies, focusing on the Principle of Conceptual Overlap. It also describes the importance of semantics when dealing with cases that do not fit available categories if the goal is to have useful nominal categories.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0006
- Subject:
- Sociology, Social Research and Statistics
This chapter examines David Hume's two definitions of cause in the context of quantitative and qualitative research. The two definitions can be found in Hume's quotation from Enquiries Concerning ...
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This chapter examines David Hume's two definitions of cause in the context of quantitative and qualitative research. The two definitions can be found in Hume's quotation from Enquiries Concerning Human Understanding, and Concerning the Principles of Morals: “We may define a cause to be an object followed by another, and where all the objects, similar to the first, are followed by objects similar to the second [definition 1]. Or, in other words, where, if the first object had not been, the second never would have existed [definition 2].” Hume's phrase “in other words” makes it appear as if definition 1 and definition 2 are equivalent, when in fact they represent quite different approaches. The chapter considers how Hume's definition 2, which it calls the “counterfactual definition,” and definition 1, the “constant conjunction definition,” are related to understandings of causation in the qualitative and quantitative research traditions.Less
This chapter examines David Hume's two definitions of cause in the context of quantitative and qualitative research. The two definitions can be found in Hume's quotation from Enquiries Concerning Human Understanding, and Concerning the Principles of Morals: “We may define a cause to be an object followed by another, and where all the objects, similar to the first, are followed by objects similar to the second [definition 1]. Or, in other words, where, if the first object had not been, the second never would have existed [definition 2].” Hume's phrase “in other words” makes it appear as if definition 1 and definition 2 are equivalent, when in fact they represent quite different approaches. The chapter considers how Hume's definition 2, which it calls the “counterfactual definition,” and definition 1, the “constant conjunction definition,” are related to understandings of causation in the qualitative and quantitative research traditions.
Gary Goertz and James Mahoney
- Published in print:
- 2012
- Published Online:
- October 2017
- ISBN:
- 9780691149707
- eISBN:
- 9781400845446
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691149707.003.0015
- Subject:
- Sociology, Social Research and Statistics
This chapter considers the typical modes of generalization used in the qualitative and quantitative research traditions. Generalization can be descriptive or causal. A descriptive generalization ...
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This chapter considers the typical modes of generalization used in the qualitative and quantitative research traditions. Generalization can be descriptive or causal. A descriptive generalization often involves one variable that “describes” some state of affairs within a population of cases. By contrast, a causal generalizations always involves at least two variables, A and B. Causal generalizations ideally specify the form and strength of the relationship between A and B within a population of cases. The two research cultures have trouble seeing and analyzing each other's typical kind of generalization. The chapter first examines generalizations in qualitative research before discussing the use of 2 x 2 tables to present set-theoretic generalizations. It then explains a well-known problem in statistical analysis involving the so-called “perfect predictors” and concludes with an assessment of the statistical significance of control variables.Less
This chapter considers the typical modes of generalization used in the qualitative and quantitative research traditions. Generalization can be descriptive or causal. A descriptive generalization often involves one variable that “describes” some state of affairs within a population of cases. By contrast, a causal generalizations always involves at least two variables, A and B. Causal generalizations ideally specify the form and strength of the relationship between A and B within a population of cases. The two research cultures have trouble seeing and analyzing each other's typical kind of generalization. The chapter first examines generalizations in qualitative research before discussing the use of 2 x 2 tables to present set-theoretic generalizations. It then explains a well-known problem in statistical analysis involving the so-called “perfect predictors” and concludes with an assessment of the statistical significance of control variables.
