Chapter 6

The Nature of Quantitative Research

Bryman: Social Research Methods: 3e

Authored by Susie Scott

The stages of quantitative research

• Theory/hypothesis• Research design• Devise measures of concepts• Select site and sample• Collect data• Code and analyse data• Write up

See pages 140-141

Concepts and their measurement

• concepts = “categories for the organisation of ideas and observations” (Bulmer, 1984: 43)

• may provide explanations of social phenomena

• may represent things we want to explain

• measurements – delineate fine differences between people/cases– consistent and reliable– more precise estimates of the degree of relatedness

between concepts

See page 143

Indicators of concepts

• produced by the operational definition of a concept

• less directly quantifiable than measures

• common sense understandings of the form a concept might take

• multiple-indicator measures– concept may have different dimensions

See page 144

Reliability

• Stability over time– test-retest method (correlation between measure on different

occasions)

• Internal reliability– split-half method (correlation between measures on two

halves of a scale)– Cronbach’s alpha

• Inter-observer consistency– agreement between different researchers

See pages 149-150

Validity

• Measurement validity:– Face validity

– Concurrent validity

– Predictive validity

– Construct validity

– Convergent validity

• Validity presupposes reliability

(but not vice versa)

See pages 151-155

The main preoccupations of quantitative researchers

• 1. Measurement– can a concept be quantified?– comparisons between measures– changes in a variable over time

• 2. Causality– explanations of social phenomena– causal relationships between independent and

dependent variables– inference only in cross-sectional designs

See pages 155-156

The main preoccupations of quantitative researchers

• 3. Generalization– can the results be applied to individuals beyond the sample?– aim to generalize to target population– requires representative sample (random, probability sample)

• 4. Replication– detailed description of procedures allows other researchers

to replicate study– low incidence of published replications

See pages 156-158

Criticisms of quantitative research

• failure to distinguish between objects in the natural world and social phenomena

• artificial and spurious sense of precision and accuracy– presumed connection between concepts and

measures

– Cicourel (1964) ‘measurement by fiat’

– respondents make different interpretations of questions and other research tools

See page 159

Criticisms of quantitative research

• lack of ecological validity– reliance on instruments and measurements– little relevance to participants’ everyday lives– variation in the meaning of concepts to each individual

• static view of social life– relationships between variables– ignores processes of human definition and

interpretation (Blumer, 1956)

See page 160

Is it always like this?

• quantitative research design is anideal-typical approach

• useful as a guide of good practice

• but discrepancy between ideal type and actual practice of social research

• pragmatic concerns mean that researchers may not adhere rigidly to these principles

See page 160

Reverse operationism

Bryman (1988)• quantitative research is usually deductive

(operational definition of concepts)• but measurements can sometimes lead to

inductive theorising• example: factor analysis

– groups of indicators cluster together and suggest a common factor

– e.g. personality trait research

See page 160

Reliability and validity testing

• published accounts of quantitative research rarely report evidence of reliability and validity (Podsakoff & Dalton, 1987)

• researchers are primarily interested in the substantive content and findings of their research

• running tests of reliability and validity may seem an unappealing alternative!

• but researchers remain committed to the principles of good practice

See pages 161-162