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Chapter 6: Qualitative and Quantitative Research Designs Introduction Triangulation Qualitative and Quantitative Research Orientations Qualitative Design Issues Quantitative Design Issues Conclusion

INTRODUCTION This chapter begins Part Two – Planning and Preparation (Design, Measurement, Sampling) Quantitative researchers are more concerned about these issues [AS ADVANCED PLANNING] because deductive approach requires detailed planning before data collection and analysis Qualitative researchers [ARE ALSO CONCERNED ABOUT THESE ISSUES, BUT CAN MAKE ADJUSTMENTS DURING THE PROJECT]

[Qualitative and Quantitative Research] Qualitative: gathers lots of information about one, two, or a few units of analysis (people, groups, organizations, events, etc.), in depth, detail, and context –Data typically are words Quantitative: gathers less information per unit, but studies far more units –Data typically are numbers

Triangulation Is looking at something from different viewpoints of measures: multiple measures of the same phenomenon of observers of theory: is multiple theoretical perspectives used during planning or analysis of the setting. of method is the mixing of multiple styles that may be qualitative and quantitative.

Qualitative and Quantitative Orientations Both collect and analyze data systematically hard vs. soft data Different assumptions about social life and how to study –Qualitative: interpretive or critical social science –Quantitative: positivist Technocratic and transcendent perspectives –Technocratic: researcher as expert, goal is discover universal laws –Transcendent: more empowering, often starting with viewpoint of those being studied

Reconstructed Logic and Logic in Practice Reconstructed logic –More typical of quantitative research –Idealized, formal, step-by-step Logic in practice –More typical of qualitative research –More ‘messy,’ varies by project, more craft and fewer rules

Linear and Nonlinear Paths Linear: straight line – typical of quantitative research –See p. 13, figure 1.1 Nonlinear: typical of qualitative research

Objectivity and Integrity What does it mean to be fair, honest? Quantitative research: –Often presents itself as ‘objective’ –Emphasis on replicability Qualitative research –Recognizes subjective element in research –Emphasis on trustworthiness Detail, plausibility in reporting helps establish this

Preplanned and Emergent Research Questions All research begins with a topic Research also requires (a) question(s): –Qualitative: original question can be very broad and general; new, more focused questions may emerge –Typical questions: what is it like to be...?, how did this condition or social situation develop? –Quantitative: usually begins with more specific question and hypothesis (hypotheses)

How to Develop a Research Question See box 6.3, page 144

Ways to Select a Topic Personal experience Curiosity based on current events State of knowledge in field Solving a problem Social premiums Personal values Everyday experiences

Narrowing Down a Topic Examine the literature. Talk with others. Limit analysis to a specific context. Define the aim and outcomes.

Qualitative Design Issues The Language of Cases and Contexts

Grounded Theory vs. Reconstruction of Theory Grounded theory begins with a question and little else. Theory is developed inductively Reconstruction of theory begins with a theory, uses qualitative research to reconstruct all or part of the theory

The Context is Critical Social context Meaning context Temporal context

Bricolage when a qualitative researcher draws on a variety of sources, making do with whatever is at hand, mixing diverse approaches, and assembling bits and pieces.

The Case and Process The Case Process

Interpretation First-order: what the actors (those being studied) think, feel, etc. Second-order: researcher’s reconstruction of this Third-order: general theoretical importance of findings

Interpretation in Qualitative Research Interpretation is the act of assigning significance or coherent meaning by translating and making understandable the data that has been collected.

Quantitative Design Issues Variables are measures of a concept that take two or more values, such as male or female. Attributes are the values or categories of a variable. Male is an attribute of the variable gender. The independent variable is the presumed cause, and the factor that precedes the effect in time. The dependent variable is the effect or outcome that is presumed to be impacted, and follows the cause in time. Intervening variables come between the independent and dependent variables.

Causal Hypotheses The causal hypothesis has at least two variables. It expresses a cause-effect relationship. It is expressed as a prediction or expected future outcome. It is logically linked to theories and the research question. It is falsifiable, or capable of being tested against empirical evidence.

Ways to State Causal Hypotheses A presumed causal (independent) variable, such as religious attendance: (1) causes, (2) leads to, (3) is related to, (4) influences, (5) is associated with, (6) produces, (7) reduces, (8) increases or decreases divorce (rates).

Null Hypothesis The null hypothesis normally states the negation of the relationship proposed in the research hypothesis. If a research hypothesis stated: “Males are more likely than females to repeat juvenile offenses.” The null would state: “There is no relationship between the sex of the offender and number of repeat offenses.”

Logical Errors in Causal Explanation Tautology is a form of fallacious circular reasoning. Sally is conservative because she believes in less regulation. While this may be true, her conservativeness is not caused by her attitude toward regulation. Teleology are causes that are associated with an ultimate purpose or goal. “Crime occurs because humans are destined to be evil …” is teleological. This violates the principle that the cause precedes the effect in time.

Logical errors continued…. Ecological fallacy arises from a mismatch of units of analysis when moving from a larger to a smaller unit. Knowing the vote totals for a particular polling district does not allow one to conclude how any one person voted. Reductionism is a mismatch in units of analysis when moving from smaller to larger. Knowing how some individuals in an organization behave does not allow one to conclude the entire organization behaves in a certain way.

Logical errors continued… Spuriousness occurs when two variables are associated but not causally related. The statistical association between air conditioning and ice cream cones sales is spurious, not causal.

Research Questions Bad: Is child abuse a problem? Good: Has the incidence of child abuse changed in the last three years in Missouri? Bad: Do social workers affect delinquency? Good: Has the incidence of delinquency changed among caseloads of graduate level social workers compared to those holding an undergraduate degree in Milwaukee?