1932

Abstract

We present a revision of latent state-trait (LST-R) theory with new definitions of states and traits. This theory applies whenever we study the consistency of behavior, its variability, and its change over time. States and traits are defined in terms of probability theory. This allows for a seamless transition from theory to statistical modeling of empirical data. LST-R theory not only gives insights into the nature of latent variables but it also takes into account four fundamental facts: Observations are fallible, they never happen in a situational vacuum, they are always made using a specific method of observations, and there is no person without a past. Although the first fact necessitates considering measurement error, the second fact requires allowances for situational fluctuations. The third fact implies that, in the first place, states and traits are method specific. Furthermore, compared to the previous version of LST theory (see, e.g., Steyer et al. 1992, 1999), our revision is based on the notion of a person-at-time-t. The new definitions in LST-R theory have far-reaching implications that not only concern the properties of states, traits, and the associated concepts of measurement errors and state residuals, but also are related to the analysis of states and traits in longitudinal observational and intervention studies.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-clinpsy-032813-153719
2015-03-28
2024-12-11
Loading full text...

Full text loading...

/deliver/fulltext/clinpsy/11/1/annurev-clinpsy-032813-153719.html?itemId=/content/journals/10.1146/annurev-clinpsy-032813-153719&mimeType=html&fmt=ahah

Literature Cited

  1. Anastasi A. 1983. Traits, states, and situations: a comprehensive view. Principles of Modern Psychological Measurement H Wainer, S Messick 345–56 Hillsdale, NJ: Erlbaum [Google Scholar]
  2. Bollen KA. 2002. Latent variables in psychology and the social sciences. Annu. Rev. Psychol. 53:605–34 [Google Scholar]
  3. Bollen KA, Curran PJ. 2006. Latent Curve Models: A Structural Equation Perspective. Hoboken, NJ: Wiley [Google Scholar]
  4. Cole DA, Martin NC, Steiger JH. 2005. Empirical and conceptual problems with longitudinal trait-state models: introducing a trait-state-occasion model. Psychol. Methods 10:3–20 [Google Scholar]
  5. Deinzer R, Steyer R, Eid M, Notz P, Schwenkmezger P. et al. 1995. Situational effects in trait assessment: the FPI, NEOFFI and EPI questionnaires. Eur. J. Personal. 9:1–23 [Google Scholar]
  6. Eid M. 1996. Longitudinal confirmatory factor analysis for polytomous item responses: model definition and model selection on the basis of stochastic measurement theory. Methods Psychol. Res. Online 1:65–85 [Google Scholar]
  7. Eid M, Diener E. 2006. Handbook of Multimethod Measurement in Psychology Washington, DC: Am. Psychol. Assoc. [Google Scholar]
  8. Eid M, Hoffmann L. 1998. Measuring variability and change with an item response model for polytomous variables. J. Educ. Behav. Stat. 23:193–215 [Google Scholar]
  9. Eid M, Langeheine R. 1999. Measuring consistency and occasion specificity with latent class models: a new model and its application to the measurement of affect. Psychol. Methods 4:100–16 [Google Scholar]
  10. Eid M, Schneider C, Schwenkmezger P. 1999. Do you feel better or worse? The validity of perceived deviations of mood states from mood traits. Eur. J. Personal. 13:283–306 [Google Scholar]
  11. Geiser C, Keller B, Lockhart G. 2013. First versus second order latent growth curve models: Some insights from latent state-trait theory. Struct. Equ. Model. 20:3479–503 [Google Scholar]
  12. Geiser C, Lockhart G. 2012. A comparison of four approaches to account for method effects in latent state-trait analyses. Psychol. Methods 17:2255–83 [Google Scholar]
  13. Guttman L. 1955. The determinacy of factor score matrices with implications for five other basic problems of common-factor theory. Br. J. Stat. Psychol. 8:65–81 [Google Scholar]
  14. Hagemann D, Hewig J, Seifert J, Naumann E, Bartussek D. 2005. The latent state-trait structure of resting EEG asymmetry: replication and extension. Psychophysiology 42:740–52 [Google Scholar]
  15. Jensen AR. 1983. The definition of intelligence and factor-score indeterminacy. Behav. Brain Sci. 6:313–15 [Google Scholar]
  16. Kirschbaum C, Steyer R, Eid M, Patalla U, Schwenkmezger P, Hellhammer DH. 1990. Cortisol and behavior: 2. Application of a latent state-trait model to salivary cortisol. Psychoneuroendocrinology 15:297–307 [Google Scholar]
  17. Mayer A, Steyer R, Mueller H. 2012. A general approach to defining latent growth components. Struct. Equ. Model. 19:513–33 [Google Scholar]
  18. McArdle JJ. 2009. Latent variable modeling of differences and changes with longitudinal data. Annu. Rev. Psychol. 60:577–605 [Google Scholar]
  19. McDonald RP. 1974. The measurement of factor indeterminacy. Psychometrika 39:203–22 [Google Scholar]
  20. Meredith M, Tisak J. 1990. Latent curve analysis. Psychometrika 55:107–22 [Google Scholar]
  21. Meredith W. 1993. Measurement invariance, factor analysis and factorial invariance. Psychometrika 58:525–43 [Google Scholar]
  22. Raykov T. 1999. Are simple change scores obsolete? An approach to studying correlates and predictors of change. Appl. Psychol. Meas. 23:120–26 [Google Scholar]
  23. Schmitt MJ, Steyer R. 1993. A latent state-trait model (not only) for social desirability. Pers. Individ. Differ. 14:519–29 [Google Scholar]
  24. Steyer R. 1988. Experiment, Regression und Kausalität. Die logische Struktur kausaler Regressionsmodelle [Experiment, regression, and causality. The logical structure of causal regression models]. Habilitation thesis, Univ. Trier, Trier, Germany [Google Scholar]
  25. Steyer R, Eid M, Schwenkmezger P. 1997. Modeling true intraindividual change: true change as a latent variable. Methods Psychol. Res. Online 2:21–33 [Google Scholar]
  26. Steyer R, Ferring D, Schmitt MJ. 1992. States and traits in psychological assessment. Eur. J. Psychol. Assess. 8:79–98 [Google Scholar]
  27. Steyer R, Geiser C, Fiege C. 2012. Latent state-trait models. APA Handbook of Research Methods in Psychology H Cooper , pp. 291–308 Washington, DC: Am. Psychol. Assoc. [Google Scholar]
  28. Steyer R, Majcen AM, Schwenkmezger P, Buchner A. 1989. A latent state-trait anxiety model and its application to determine consistency and specificity coefficients. Anxiety Res. 1:281–99 [Google Scholar]
  29. Steyer R, Mayer A, Fiege C. 2014. Causal inference on total, direct, and indirect effects. Encyclopedia of Quality of Life and Well-Being Research AC Michalos, pp. 606–31. Dordrecht, Neth.: Springer [Google Scholar]
  30. Steyer R, Schmitt M, Eid M. 1999. Latent state-trait theory and research in personality and individual differences. Eur. J. Personal. 13:389–408 [Google Scholar]
  31. Steyer R, Schwenkmetzger P, Auer A. 1990. The emotional and cognitive components of trait anxiety: a latent state-trait model. Personal. Individ. Differ. 11:125–34 [Google Scholar]
  32. Tanzer NK. 1998. Assessment of Domain-Specificity in School-Related Likert-Type Inventories: Conceptual Issues, Psychometric Approaches, and Cross-Cultural Evidence Graz, Austria: Karl-Franzens-Universität [Google Scholar]
  33. Tisak J, Tisak MS. 2000. Permanency and ephemerality of psychological measures with application to organizational commitment. Psychol. Methods 5:175–98 [Google Scholar]
  34. Widaman K, Reise S. 1997. Exploring the measurement invariance of psychological instruments: applications in the substance use domain. The Science of Prevention: Methodological Advances from Alcohol and Substance Abuse Research K Bryant, M Windle, S West 281–324 Washington, DC: Am. Psychol. Assoc. [Google Scholar]
  35. Williams JS. 1978. A definition for the common-factor analysis model and the elimination of problems of factor score indeterminacy. Psychometrika 43:293–306 [Google Scholar]
/content/journals/10.1146/annurev-clinpsy-032813-153719
Loading
/content/journals/10.1146/annurev-clinpsy-032813-153719
Loading

Data & Media loading...

Supplementary Data

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error