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Quantitative and Qualitative Research, Debate About
The debate about quantitative and qualitative research is concerned with the question of whether the two research strategies should be considered contrasting epistemological positions or whether they are better conceptualized as simply referring to different clusters of techniques of data collection and analysis. The issue is very significant in terms of the prospects for multistrategy research. If quantitative and qualitative research are viewed as distinctive and largely irreconcilable epistemologies, multistrategy research is very difficult to envision. On the other hand, if they are viewed as different methods of data collection and analysis, research combining quantitative and qualitative research (i.e., multistrategy research) is easier to imagine.
The epistemological version of the debate has two major forms (Bryman, 2001). One is the embedded methods argument. This argument asserts that any research method is rooted in epistemological commitments. Thus, to choose to conduct research using a self-administered questionnaire is not just seeking answers to a research question in a certain way; the choice also entails a commitment to the epistemological (and ontological) principles with which it is deemed to be associated (for example, positivism). When Hughes (1990) writes that “every research tool or procedure is inextricably embedded in commitments to particular visions of the world and to knowing that world” (p. 11), he was essentially taking up the embedded methods argument.
The other form of the epistemological version of the debate is the paradigm argument. Drawing on Kuhn’s (1970) notion of the paradigm, this argument depicts quantitative and qualitative research as paradigms. As such, epistemological assumptions, values, and methods are viewed as inseparable within each of the two paradigms. In addition, because paradigms are deemed to be incapable of reconciliation, quantitative and qualitative research cannot be reconciled. This form of the epistemological version shares with the embedded methods argument the view that methods of research are linked to epistemological positions, but it goes further in viewing quantitative and qualitative research more generally as incommensurable.
Although the epistemological version of the debate about quantitative and qualitative research still has adherents who rail against the notion that the two research strategies can be combined at anything more than the most superficial level (e.g., Sale, Lohfeld, & Brazil, 2002), this position has increasingly given way to the technical version of the debate. Writers associated with the technical version recognize that quantitative and qualitative research have connections with epistemological and ontological assumptions but do not see these connections as inevitable. In other words, research methods can serve different masters, so that a “research method from one research strategy is viewed as capable of being pressed into the service of another” (Bryman, 2001, p. 446).
This softening among most writers in their views about quantitative and qualitative research, whereby the technical version of the debate is tending to hold sway, has almost certainly led to an increase in multistrategy research and certainly in its acceptability.
References
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- Analysis of Variance
- Association and Correlation
- Association
- Association Model
- Asymmetric Measures
- Biserial Correlation
- Canonical Correlation Analysis
- Correlation
- Correspondence Analysis
- Intraclass Correlation
- Multiple Correlation
- Part Correlation
- Partial Correlation
- Pearson's Correlation Coefficient
- Semipartial Correlation
- Simple Correlation (Regression)
- Spearman Correlation Coefficient
- Strength of Association
- Symmetric Measures
- Basic Qualitative Research
- Basic Statistics
- F Ratio
- N(n)
- t-Test
- X¯
- Y Variable
- z-Test
- Alternative Hypothesis
- Average
- Bar Graph
- Bell-Shaped Curve
- Bimodal
- Case
- Causal Modeling
- Cell
- Covariance
- Cumulative Frequency Polygon
- Data
- Dependent Variable
- Dispersion
- Exploratory Data Analysis
- Frequency Distribution
- Histogram
- Hypothesis
- Independent Variable
- Measures of Central Tendency
- Median
- Null Hypothesis
- Pie Chart
- Regression
- Standard Deviation
- Statistic
- Causal Modeling
- Discourse/Conversation Analysis
- Econometrics
- Epistemology
- Ethnography
- Evaluation
- Event History Analysis
- Experimental Design
- Factor Analysis and Related Techniques
- Feminist Methodology
- Generalized Linear Models
- Historical/Comparative
- Interviewing in Qualitative Research
- Latent Variable Model
- Life History/Biography
- Log-Linear Models (Categorical Dependent Variables)
- Longitudinal Analysis
- Mathematics and Formal Models
- Measurement Level
- Measurement Testing and Classification
- Multilevel Analysis
- Multiple Regression
- Qualitative Data Analysis
- Sampling in Qualitative Research
- Sampling in Surveys
- Scaling
- Significance Testing
- Simple Regression
- Survey Design
- Time Series
- ARIMA
- Box-Jenkins Modeling
- Cointegration
- Detrending
- Durbin-Watson Statistic
- Error Correction Models
- Forecasting
- Granger Causality
- Interrupted Time-Series Design
- Intervention Analysis
- Lag Structure
- Moving Average
- Periodicity
- Serial Correlation
- Spectral Analysis
- Time-Series Cross-Section (TSCS) Models
- Time-Series Data (Analysis/Design)
- Trend Analysis
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