Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-25T12:03:24.705Z Has data issue: false hasContentIssue false

Constructing Personality Maps, Mapping Personality Constructs: Multidimensional Scaling Recovers the Big Five Factors from Internal and External Structure

Published online by Cambridge University Press:  10 April 2014

David Bimler
Affiliation:
Massey University, New Zealand
John Kirkland*
Affiliation:
Massey University, New Zealand
*
Address correspondence concerning this article to John Kirkland, School of Arts, Development and Health Education, College of Education, Massey University, Private Bag 11-222, Palmerston North, New Zealand. E-mail: [email protected]

Abstract

This report examines the structure of similarities underlying the lexicon of personality-trait description, when “similarity” is defined and measured in terms of (a) semantic judgment and (b) covariance in actual use. A lexicon of 60 trait adjectives was examined, using several procedures for collecting semantic judgments. Similarity data of both kinds were analyzed with multidimensional scaling (MDS) to provide a parsimonious representation of underlying structure. The convergence between semantic judgments and covariance within trait-attribution data was substantial; both kinds of data evinced the same structure when collected for subsets of adjectives. Canonical correlation was employed to find the number of dimensions shared across MDS solutions. Interpretation of the results was facilitated by individual-differences MDS, which can select an optimal set of underlying dimensions, and at the same time accommodate the differences between data sets that arise when data-collection procedures differ in the relative emphasis they place upon those dimensions. We interpret the small number and shared nature of the dimensions by arguing that the lexicon's structure relates to trait perception rather than personality structure per se, even when probed with trait-attribution covariance.

Este trabajo examina la estructura de las similitudes subyacentes al léxico de la descripción de los rasgos de personalidad, cuando “similitud” se define y se mide en términos de: (a) juicio semántico y (b) covarianza en el uso actual. Se examinó un léxico de 60 adjetivos de rasgos, empleando varios procedimientos para recoger juicios semánticos. Los datos de similitud de ambos tipos se analizaron con escalonamiento multidimensional (EMD) para obtener una representación parsimoniosa de la estructura subyacente. La convergencia entre los juicios semánticos y la covarianza rasgo-datos atribucionales era sustancial; ambos tipos de datos mostraban la misma estructura cuando se recogían para subconjuntos de adjetivos. Se empleó la correlación canónica para encontrar el número de dimensiones compartidas por las soluciones EMD. La EMD de diferencias individuales facilitó la interpretación de los resultados porque puede seleccionar un conjunto óptimo de dimensiones subyacentes y, al mismo tiempo, adaptar las diferencias entre los conjuntos de datos que emergen cuando los procedimientos de recogida de datos difieren con respecto al énfasis relativo que se concede a dichas dimensiones. Nosotros interpretamos el pequeño número y la naturaleza compartida de las dimensiones arguyendo que la estructura del léxico se relaciona más con la percepción de los rasgos que con la estructure de la personalidad en sí, incluso cuando se analiza mediante la covarianza rasgo-atribución.

Type
Articles
Copyright
Copyright © Cambridge University Press 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bijmold, T.H.A., & Wedel, M. (1999). A comparison of multidimensional methods for perceptual mapping. Journal of Marketing Research, 36, 277285.CrossRefGoogle Scholar
Bimler, D.L., & Kirkland, J. (1999). Capturing images in a net: Perceptual modelling of product descriptors using sorting data. Marketing Bulletin, 10, 1123.Google Scholar
Block, J. (1961). The Q-sort method in personality assessment and psychological research. Springfield, IL: Charles C. Thomas (reprinted 1978, Palo Alto, CA: Consulting Psychologists Press).CrossRefGoogle Scholar
Block, J. (2001). Millennial contrarianism: The five-factor approach to personality description 5 years later. Journal of Research in Personality, 35, 98107.CrossRefGoogle Scholar
Borkenau, P. (1992). Implicit personality and the five-factor model. Journal of Personality, 62, 295327.CrossRefGoogle Scholar
Carroll, J.B. (2002). The Five-Factor personality model: How complete and satisfactory is it? In Braun, H., Jackson, D.N., & Wiley, D.E. (Eds.), The role of constructs in psychological and educational measurement (pp. 97126). Mahwah, NJ: Erlbaum.Google Scholar
Church, A.T., & Katigbak, M.S. (1989). Internal, external, and self-report structure of personality in a non-Western culture: An investigation of cross-language and cross-cultural generalizability. Journal of Personality & Social Psychology, 57, 857872.CrossRefGoogle Scholar
Dabady, M., Bell, M., & Kihlstrom, J.F. (1999). Person memory: Organization of behaviors by traits. Journal of Research in Personality, 33, 369377.CrossRefGoogle Scholar
D'Andrade, R.G. (1965). Trait psychology and componential analysis. American Anthropologist, 67, 215228.CrossRefGoogle Scholar
Davison, M.L., & Skay, C.L. (1991). Multidimensional scaling and factor models of test and item responses. Psychological Bulletin, 110, 551556.CrossRefGoogle Scholar
Goldberg, L.R. (1992). The development of markers for the Big-Five factor structure. Psychological Assessment, 4, 2642.CrossRefGoogle Scholar
Graziano, W G., Jensen-Campbell, L.A., Steele, R.G., & Hair, E.C. (1998). Unknown words in self-reported personality: Lethargic and Provincial in Texas. Personality & Social Psychology Bulletin, 24, 893905.CrossRefGoogle Scholar
Guttman, L. (1966). Order analysis of correlation matrices. In Cattell, R.B. (Ed.), Handbook of multivariate experimental psychology (pp. 438458). Chicago: Rand McNally.Google Scholar
Hakel, M.D. (1969). Significance of implicit personality theories for personality research and theory. Proceedings of the 77th Convention of the APA, 4, 403404.Google Scholar
Harris, R.J. (1975). A primer of multivariate statistics. New York: Academic Press.Google Scholar
Hofstee, W.K.B., de Raad, B., & Goldberg, L.R. (1992). Integration of the Big Five and circumplex approaches to trait structure. Journal of Personality & Social Psychology, 63, 146163.CrossRefGoogle ScholarPubMed
Johnson, J.A., & Ostendorf, F. (1993). Clarification of the Five-Factor Model with the Abridged Big Five Dimensional Circumplex. Journal of Personality & Social Psychology, 65, 563576.CrossRefGoogle Scholar
Kruskal, J.B., & Wish, M. (1978). Multidimensional scaling. Sage University Paper Series on Quantitative Applications in the Social Sciences, 07-011. Beverly Hills, CA: Sage.CrossRefGoogle Scholar
Maraun, M. D. (1997). Appearance and reality: Is the Big Five the structure of trait descriptors? Personality & Individual Differences, 22, 629647.CrossRefGoogle Scholar
Mehrabian, A. (1995). Relationships among three general approaches to personality description. Journal of Personality, 129, 565581.Google ScholarPubMed
Osgood, C.E. (1971). Explorations in semantic space: A personal diary. Journal of Social Issues, 27, 564.CrossRefGoogle Scholar
Passini, F.T., & Norman, W.T. (1966). A universal conception of personality structure? Journal of Personality & Social Psychology, 4, 4449.CrossRefGoogle ScholarPubMed
Peabody, D., & Goldberg, L.R. (1989). Some determinants of factor structures from personality-trait descriptors. Journal of Personality & Social Psychology, 57, 552567.CrossRefGoogle ScholarPubMed
Shepard, R., & Cooper, L. (1992). Representation of colors in the blind, color-blind, and normally sighted. Psychological Science, 3, 97103.CrossRefGoogle Scholar
Sherman, R.C. (1972). Individual differences in perceived trait relationships as a function of dimensional salience. Multivariate Behavioral Research, 7, 109129.CrossRefGoogle ScholarPubMed
Shweder, R.A., & D'Andrade, R.G. (1980). The systematic distortion hypothesis. New directions for methodology of social and behavioral science, 4, 338. San Francisco: Jossey-Bass.Google Scholar
Sneed, C.D., McCrae, R.R., & Funder, D.C. (1998). Lay conceptions of the five-factor model and its indicators. Personality & Social Psychology Bulletin, 24, 115126.CrossRefGoogle Scholar
Takane, Y. (1978). A Maximum Likelihood method for nonmetric multidimensional scaling: I. The case in which all empirical pairwise orderings are independent – Theory. Japanese Psychological Research, 20, 717.CrossRefGoogle Scholar
Trapnell, P.D., & Wiggins, J.S. (1990). Extension of the Interpersonal Adjective Scales to include the Big Five dimensions of personality. Journal of Personality & Social Psychology, 59, 781790.CrossRefGoogle Scholar
Vonk, R. (1995). Effects of inconsistent behaviors on personal impressions: A multidimensional study. Personality & Social Psychology Bulletin, 21, 674685.CrossRefGoogle Scholar
Wiggins, J.S. (1973). Personality and prediction: Principles of personality assessment. Reading, MA: Addison-Wesley.Google Scholar