validity
DESCRIPTION
A criterion in measurement research referring to the degree to which an instrument measures what it is intending to measure.
A criterion in measurement research referring to the degree to which an instrument measures what it is intending to measure.
KEY INSIGHTS
Validity measurement is one of the three standard measurement criteria (in addition to reliability and sensitivity) that are drawn upon in facilitating the conduct of high-quality research (Churchill 1979). There are a number of different validity measures used in marketing research, including those referred to by the following terms:
Validity measurement is one of the three standard measurement criteria (in addition to reliability and sensitivity) that are drawn upon in facilitating the conduct of high-quality research (Churchill 1979). There are a number of different validity measures used in marketing research, including those referred to by the following terms:
A priori validity—see face validity (below).
Concurrent validity—a type of criterion validity in that it is validity based on the degree to which a measurement approach predicts an outside criterion, or established standard against which other things can be compared and evaluated, where such criterion measures are obtained at the same time as the measurement.
Consensual validity—the degree to which there is agreement of validity among a knowledgeable community or group of individuals.
Construct validity—the degree to which a measurement approach actually measures the underlying theoretical construct it is supposed to be measuring.
Content validity—based on expert judgment, the degree to which a measurement scale contains items which experts consider to be representative of that which is to be measured.
Convergent validity—validity that is based on hypotheses and examinations of the overlap between different measurement approaches which are presumed to measure the same construct.
Criterion validity—validity based on the degree to which a measurement approach predicts an outside criterion, or established standard against which other things can be compared and evaluated.
Discriminant validity—also known as divergent validity, discriminant validity is the opposite of convergent validity as it is validity based on the degree to which the construct fails to correlate with other theoretically distinct constructs.
Divergent validity—see discriminant validity (above).
Ecological validity—the degree to which the settings, methods, and materials used in a study approximate the larger, real-life situation that is being studied.
External validity—the degree to which the results of the findings of a study are generalizable in that they are relevant to subjects and settings beyond those used in the study.
Face validity—also called a priori validity, the degree to which, by the face of it, a measure seems to make sense in that it looks like it is going to measure what it is intended to measure on the basis of reason as opposed to experience.
Factorial validity—a form of construct validity (see above) established through factor analysis where multiple measurement approaches purported to be measuring the same constructs are factor analyzed to determine the degree to which they share common variance and thus can be said to be tapping into the same underlying construct.
Incremental validity—the degree to which a measure is able to explain or predict a phenomenon of interest, relative to other measures having the same purpose.
Internal validity—the degree to which an experiment is able to demonstrate a causal relationship between two variables, i.e. that ‘cause’ precedes ‘effect’ in time, ‘cause’ and ‘effect’ are shown to be related, and there is a lack of alternative explanations (e.g. problems in the research design) for the relationship observed between the two variables.
Nomological validity—the degree to which the correlation between a measure and another related construct behaves as expected in theory, in that a construct predicts measures of other constructs from the perspective of a formal theoretical network of relationships.
Population validity—the degree to which the findings of a study are generalized from the sample to the larger population.
Predictive validity—a type of criterion validity in that it is validity based on the degree to which a measurement approach predicts an outside criterion, or established standard against which other things can be compared and evaluated, where such criterion measures are obtained at a time after the measurement.
Statistical validity—the degree to which appropriate choices are made concerning the statistical methods and tests used in relation to the measurement approach and the nature of the data collection process.
Trait validity—the degree to which a construct and its measures are in accordance with theory only at the level of a single trait or distinguishing characteristic (i.e. theory that does not consider the
interrelationships of constructs within a nomological network).
interrelationships of constructs within a nomological network).
IMPLICATIONS
A greater knowledge of all measures of validity can clearly be beneficial in assisting the marketing researcher with designing, implementing, and evaluating marketing research—whether one’s own or those of others— for appropriate usability by the marketer. While some measures of validity may be potentially more of an issue in quantitative research and others more of an issue in qualitative research, understanding better the many different perspectives on measurement validity further allows the marketing researcher to conduct tradeoffs in the selection and use of a wide range of marketing research approaches.
A greater knowledge of all measures of validity can clearly be beneficial in assisting the marketing researcher with designing, implementing, and evaluating marketing research—whether one’s own or those of others— for appropriate usability by the marketer. While some measures of validity may be potentially more of an issue in quantitative research and others more of an issue in qualitative research, understanding better the many different perspectives on measurement validity further allows the marketing researcher to conduct tradeoffs in the selection and use of a wide range of marketing research approaches.
APPLICATION AREAS AND FURTHER READINGS
Marketing Research
Peter, J. P. (1981). ‘Construct Validity: A Review of Basic Issues and Marketing Practices,’ Journal of Marketing Research 18, 133–145.
Peter, J. P. (1981). ‘Construct Validity: A Review of Basic Issues and Marketing Practices,’ Journal of Marketing Research 18, 133–145.
Loyd, B. H., and Gressard, C. (1984). ‘Reliability and Factorial Validity of Computer Attitude Scales,’ Educational and Psychological Measurement, 44, 501–505.
John, George, and Reve, Torger (1982). ‘The Reliability and Validity of Key Informant Data from Dyadic Relationships in Marketing Channels,’ Journal of Marketing Research, 19(4), Special Issue on Causal Modeling, November, 517–524.
Ruekert, Robert W., and Churchill, Gilbert A. (1982). The Reliability and Validity of Alternative Measures of Channel Member Satisfaction. Madison: Graduate School of Business, University of Wisconsin-Madison.
Spiro, Rosann L., andWeitz, Barton A. (1990). ‘Adaptive Selling: Conceptualization, Measurement, and Nomological Validity,’ Journal of Marketing Research, 27(1), February, 61–69.
Netemeyer, Richard G., Durvasula, Srinivas, and Lichtenstein, Donald R. (1991). ‘A Cross-National Assessment of the Reliability and Validity of the CETSCALE,’ Journal of Marketing Research, 28(3), August, 320–327.
Perreault, William D., Jr., and Leigh, Laurence E. (1989). ‘Reliability of Nominal Data Based on Qualitative Judgments,’ Journal of Marketing Research, 26(2), May, 135–148.
Green, Paul E., and Srinivasan, V. (1990). ‘Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice,’ Journal of Marketing, 54(4), October, 3–19.
Malhotra, Naresh K. (1981). ‘A Scale to Measure Self-Concepts, Person Concepts, and Product Concepts,’ Journal of Marketing Research, 18(4), November, 456–464.
Peter, J. Paul, and Churchill, Gilbert A., Jr. (1986). ‘Relationships among Research Design Choices and Psychometric Properties of Rating Scales: A Meta-analysis,’ Journal of Marketing Research, 23(1), February, 1–10.
Winer, R. S. (1999). ‘Experimentation in the 21st Century: The Importance of External Validity,’ Academy of Marketing Science, 27(3), 349–358.
BIBLIOGRAPHY
Gilbert A. Churchill, Jr. (1979). ‘A Paradigm for Developing Better Measures of Marketing Constructs,’ Journal of Marketing Research, 16(1), February, 64–73.
Gilbert A. Churchill, Jr. (1979). ‘A Paradigm for Developing Better Measures of Marketing Constructs,’ Journal of Marketing Research, 16(1), February, 64–73.
Heeler, Roger M., and Ray, Michael L. (1972). ‘Measure Validation in Marketing,’ Journal of Marketing Research, 9, November, 361–370.
Brewer, M. (2000). ‘Research Design and Issues of Validity,’ in H. Reis and C. Judd (eds.), Handbook of Research Methods in Social and Personality Psychology. Cambridge: Cambridge University Press.