The personal structure of personal need for structure a mixture-distribution Rasch analysis

European Journal of Psychological Assessment

Volumn 24, Issue 1, 2008, Pages 27-34

  Meiser, Thorsten ^a,b   Machunsky, Maya ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

^b PHILIPPS UNIVERSITY MARBURG   (Germany)

Author keywords

Mixed Rasch model; Personal need for structure; Personality assessment; Rating scale model

Indexed keywords

EID: 39549102854     PISSN: 10155759     EISSN: None     Source Type: Journal    
DOI: 10.1027/1015-5759.24.1.27     Document Type: Article

References (28)

1. Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43, 561-573.
2. Andrich, D. (1982). An extension of the Rasch model for ratings providing both location and dispersion parameters. Psychometrika, 47, 105-113.
3. Borkenau, P., & Ostendorf, F. (1993). NEO-Fünf-Faktoren Inventar (NEO-FFI) [NEO-Five-Factor Inventory (NEO-FFI)]. Göttingen: Hogrefe.
4. Eid, M., & Zickar, M.J. (2007). Detecting response styles and faking in personality and organizational assessments by mixed Rasch models. In M. von Davier & C.H. Carstensen (Eds.), Multivariate and mixture distribution Rasch models. Extensions and applications (pp. 255-270). New York: Springer Science + Business Media.
5. Fischer, G.H., & Molenaar, I.W. (Eds.) (1995). Rasch models. Foundations, recent developments, and applications. New York: Springer-Verlag.
6. Machunsky, M., & Meiser, T. (2006). Personal need for structureals differenzialpsychologisches Konstrukt in der Sozialpsychologie: Psychometrische Analyse und Validierung einer deutschsprachigen PNS-Skala [Personal need for structure as a construct of dispositional differences in social psychology: Psychometric analysis and validation of a German PNS scale]. Zeitschrift für Sozialpsychologie, 37, 87-97.
7. Masters, G.N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47, 149-174.
8. McLachlan, G., & Peel, D. (2000). Finite mixture models. New York: Wiley.
9. Mislevy, R.J., & Verhelst, N. (1990). Modeling item responses when different subjects employ different solution strategies. Psychometrika, 55, 195-215.
10. Moskowitz, G.B. (1993). Individual differences in social categorization: The influence of personal need for structure on spontaneous trait inferences. Journal of Personality and Social Psychology, 65, 132-142.
11. Neuberg, S.L., & Newsom, J.T. (1993). Personal need for structure: Individual differences in the desire for simple structure. Journal of Personality and Social Psychology, 65, 113-131.
12. Perreault, S., & Bourhis, R.Y. (1999). Ethnocentrism, social identification, and discrimination. Personality and Social Psychology Bulletin, 25, 92-103.
13. Rasch, G. (1968). An individualistic approach to item analysis. In P.F. Lazarsfeld & N.W. Henry (Eds.), Readings in mathematical social science (pp. 89-107). Cambridge: MIT Press.
14. Rasch, G. (1980). Probabilistic models for some intelligence and attainment tests. Chicago: University of Chicago Press (Original published 1960, Copenhagen: Danish Institute of Educational Research).
15. Rost, J. (1988). Measuring attitudes with a threshold model drawing on a traditional scaling concept. Applied Psychological Measurement, 12, 397-409.
16. Rost, J. (1990). Rasch models in latent classes: An integration of two approaches to item analysis. Applied Psychological Measurement, 14, 271-282.
17. Rost, J. (1991). A logistic mixture distribution model for polychotomous item responses. British Journal of Mathematical and Statistical Psychology, 44, 75-92.
18. Rost, J., Carstensen, C.H., & von Davier, M. (1997). Applying the mixed Rasch model to personality questionnaires. In J. Rost & R. Langeheine (Eds.), Applications of latent trait and latent class models in the social sciences (pp. 324-332). Münster: Waxmann.
19. Rost, J., Carstensen, C.H., & von Davier, M. (1999). Sind die Big Five Rasch-skalierbar? Eine Reanalyse der NEO-FFI-Normierungsdaten. [Are the Big Five Rasch-scalable? A reanalysis of the NEO-FH norm data]. Diagnostica, 45, 119-127.
20. Schaller, M., Boyd, C., Yohannes, J., & O'Brien, M. (1995). The prejudiced personality revisited: Personal need for structure and formation of erroneous group stereotypes. Journal of Personality and Social Psychology, 68, 544-555.
21. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464.
22. Thompson, E.P., Roman, R.J., Moskowitz, G.B., Chaiken, S., & Bargh, J.A. (1994). Accuracy motivation attenuates covert priming: The systematic reprocessing of social information. Journal of Personality and Social Psychology, 66, 474-489.
23. Thompson, M.M., Naccarato, M.E., Parker, K.C.H., & Moskowitz, G.B. (2001). The personal need for structure and personal fear of invalidity measures: Historical perspectives, current applications, and future directions. In G.B. Moskowitz (Ed.), Cognitive social psychology: The Princeton symposium on the legacy and future of social cognition (pp. 19-39). Mahwah, NJ: Erlbaum.
24. von Davier, M. (1997). Bootstrapping goodness-of-fit statistics for sparse categorical data - Results of a Monte-Carlo study. Methods of Psychological Research, 2, 29-48.
25. von Davier, M. (2001). WINMIRA 2001 - A Windows program for analyses with the Rasch model, with the latent class analysis, and with the mixed Rasch model. Software distributed by Assessment Systems Corporation, USA, and Science Plus Group, Groningen, The Netherlands.
26. von Davier, M., & Carstensen, C.H. (Eds.), (in press). Multivariate and mixture distribution Rasch models. Extensions and applications. New York: Springer Science + Business Media.
27. von Davier, M., & Rost, J. (1995). Polytomous mixed Rasch models. In G.H. Fischer & I.W. Molenaar (Eds.), Rasch models. Foundations, recent developments, and applications (pp. 371-379). New York: Springer-Verlag.
28. von Davier, M., & Yamamoto, K. (2007). Mixture distribution and hybrid Rasch models. In M. von Davier & C.H. Carstensen (Eds.), Multivariate and mixture distribution Rasch models. Extensions and applications (pp. 99-115). New York: Springer-Verlag.