Week 4, Chapter 6
Chapter 6- Qualitative and Quantitative Measurement
Quantitative and Qualitative Measurement
Both qualt & quant researches use careful, systematic methods to gather high-quality data. Yet,
differences in the styles of research & the types of data mean that they approach the measurement
process differently. Designing precise ways to measure variables is a vital step in planning a study for
quant researchers. Qualt researchers use a wider variety of techniques to measure.
Differences b/w the 2 types:
1) Timing: Quant think about variables and convert them into specific actions during a planning stage
that occurs before and is separate from gathering or analyzing data.
Measurement for qualt researchers occurs in the data-collection process
2) Data itself : Quant researchers develop techniques that can produce quant data (i.e data in the form of
#s). Thus, the researcher moves from abstract ideas to specific data-collection techniques to precise
numerical info produced by the techniques. The num info is an empirical representation of the abstract
Data for qualt researchers sometimes are in the form of #s; more often, they include written or spoken
words, actions, sounds, symbols, physical objects or images. The qualt researcher doesn't convert all
observation into a single medium such as #s. Instead he/she develops many flexible, ongoing processes to
measure that leave the data in various shapes, sizes & forms.
3) How the 2 styles make such linkages: Quant researchers contemplate & reflect on concepts before
they gather any data. They construct measurement techniques that bridge concepts & data.
Qualt researchers also reflect on ideas before data collection but they develop many of their concepts
during data collection.
Parts Of The Measurement Process
Quantitative: deductive route. They begin with the abstract idea, follow with a measurement
procedure, and end with empirical data that represent the ideas
Qualitative: inductive route. They begin with empirical data, follow with abstract ideas, relate ideas
and data, and end with a mixture of ideas and data.
Quantitative and qualitative use two process in measurement: conceptualization and
Conceptualization: The process of taking a construct and refining it by giving it a conceptual or
A conceptual definition is a definition in abstract, theoretical terms. It refers to other ideas or
constructs. It involves thinking carefully, observing directly, consulting / others, readings what others
have said & trying possible defns.
Operationalization: links a conceptual definition to a specific set of measurement techniques or
procedures, the construct's operational definition.
Operational Definition: defn of a variable in terms of the specific activities to measure or indicate it
w/ empirical evidence. Could be a survey questionnaire, a way to measure symbolic content in the
mass media etc.
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Operationalization links the language of theory w/ the lang of empirical measures. Theory is full of
abstract concepts, assumptions, relationships, defns & causality. Empirical measures describe how
people concretely measure specific variables.
Quantitative Conceptualization & Operationalization
1st conceptualization then operationalization & finally application of the operational defn or
measuring to collect the data.
3 levels to consider: conceptual, operational & empirical
At the most abstract level, the researcher is interested in the causal relationship b/w 2 constructs or a
Conceptual Hypothesis: a type of hyp in which the researcher expresses variables in abstract,
conceptual terms & expresses the relationship among variables in a theoretical way.
At the level of operational defns, the researcher is interested in testing an empirical hypothesis to
determine the degree of association b/w indicators.
Empirical Hypothesis: a type of hyp in which the researcher expresses variables in specific terms &
expresses the association among the measures indicators of observable, empirical evidence.
3rd level is the concrete empirical world. If the operational indicators of variables (e.g
questionnaires) are logically linked to a construct (e.g racial discrim), they will capture what happens
in the empirical social world & relate it to the conceptual level.
Measurement process links together the 3 levels, moving deductively from the abstract to the
Qualitative Conceptualization & Operationalization
Conceptualization: a process of forming coherent theoretical definitions as one struggles to “make
sense” or organize the data and one’s preliminary ideas. As the researcher gathers & analyzes qualt
data, he/she develops new concepts, formulates defns for the concepts & considers relationships
among the concepts. Eventually, they link concepts to one another to create theoretical relationships
that may or may not be causal. Qualt researchers form the concepts as they examine their qualt data.
Operationalization: is an after-the-fact description more than a before-the-fact preplanned technique.
Data gathering occurs with or prior to full operationalization.
Reliability & Validity
Both concern how concrete measures are connected to constructs. Reliability & validity are salient b/c
constructs in social theory are often ambiguous, diffuse & not directly observable.
Reliability:The dependability or consistency of the measure of a variable
Validity: it refers to how well an idea about reality "fits" with actual reality.
Reliability & Validity in Quant Research
4 ways to increase the reliability of measures
1) Clearly conceptualize constructs: developing clear theoretical defns. Constructs should be specified
to eliminate "noise" from other constructs.
2) Increase the level of measurement: indicators at higher or more precise levels of measurements are
more likely to be reliable than less precise measures b/c the latter pick up less detailed info. If more
specific info is measured, then it is less likely that anything other than the construct will be captured.
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3) Use multiple indicators of a variable: multiple indicators of the same construct are better than 1.
Three indicators of the 1 IV construct are combined into an overall measure, A, & 2 indicators of a
DV are combined into a single measure, B.
4) Use pretests, pilot tests & replication: develop 1 or more draft of preliminary versions of a measure
& try them before applying the final versions in a hypothesis-testing situation.
Validity → Measurement Validity: refers to how well the conceptual & operational defns mesh w/
each other. The better the fit, the greater the measurement validity.
Types of Measurement Validity
1) Face Validity: it is a judgment by the scientific comm that th