Investigating change in intraindividual factor structure over time

Applied Psychological Measurement

Volumn 33, Issue 4, 2009, Pages 266-284

  Rausch, Joseph R ^a,b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b CINCINNATI CHILDREN'S HOSPITAL MEDICAL CENTER   (United States)

Author keywords

Factor structure change; Intraindividual change; Multivariate time series; P technique; TIFS model

Indexed keywords

EID: 65649085938     PISSN: 01466216     EISSN: 15523497     Source Type: Journal    
DOI: 10.1177/0146621608327802     Document Type: Article

References (59)

1. Anderson, T.W. (1963). The use of factor analysis in the statistical analysis of multiple time series. Psychometrika, 28, 1-25.
2. Atkin, R., Bray, R., Davison, M., Herzberger, S., Humphreys, L., & Selzer, U. (1977). Ability factor differentiation, grades 5 through 11. Applied Psychological Measurement, 1, 65-76.
3. Baltes, P.B., Cornelius, S.W., Spiro, A., Nesselroade, J.R., & Willis, S.L. (1980). Integration versus differentiation of fluid/crystallized intelligence in old age. Developmental Psychology, 16, 625-635.
4. Baltes, P.B., & Nesselroade, J.R. (1973). The developmental analysis of individual differences on multiple measures. In J. R. Nesselroade & H. W. Reese (Eds.), Life-span developmental psychology: Methodological issues (pp. 219-251). New York: Academic Press.
5. Baltes, P.B., Nesselroade, J.R., & Cornelius, S.W. (1978). Multivariate antecedents of structural change in development: A simulation of cumulative environmental patterns. Multivariate Behavioral Research, 13, 127-152.
6. Bickley, P.G., Keith, T.Z., & Wolfle, L.M. (1995). The three-stratum theory of cognitive abilities: Test of the structure of intelligence across the life span. Intelligence, 20, 309-328.
7. Böckenholt, U. (2005). A latent Markov model for the analysis of longitudinal data collected in continuous time: States, durations, and transitions. Psychological Methods, 10, 65-83.
8. Borsboom, D., Mellenbergh, G.J., & van Heerden, J. (2003). The theoretical status of latent variables. Psychological Review, 110, 203-219.
9. Bridges, K.M.B. (1932). Emotional development in early infancy. Child Development, 3, 324-341.
10. Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage.
11. Browne, M.W., & Nesselroade, J.R. (2005). Representing psychological processes with dynamic factor analysis: Some promising uses and extensions of autoregressive moving average time series models. In A. Maydeu-Olivares & J. J. McArdle (Eds.), Contemporary psychometrics: A festschrift for Roderick P. McDonald (pp. 415-452). Mahwah, NJ: Lawrence Erlbaum.
12. Bryk, A.S., & Raudenbush, S.W. (1987). Application of hierarchical linear models to assessing change. Psychological Bulletin, 101, 147-158.
13. Cattell, R.B. (1946). Description and measurement of personality. Yonkers-on-Hudson, NY: World Book.
14. Cattell, R.B. (1966). Patterns of change: Measurement in relation to state-dimension, trait change, lability, and process concepts. In R. B. Cattell (Ed.), Handbook of multivariate experimental psychology (pp. 355-402). Chicago: Rand McNally.
15. Coan, R.W. (1966). Child personality and developmental psychology. In R. B. Cattell (Ed.), Handbook of multivariate experimental psychology (pp. 732-752). Chicago: Rand McNally.
16. Cole, D.A., Truglio, R., & Peeke, L. (1997). Relation between symptoms of anxiety and depression in children: A multitrait-multimethod- multigroup assessment. Journal of Consulting and Clinical Psychology, 65, 110-119.
17. Collins, L.M., & Cliff, N. (1990). Using the longitudinal Guttman simplex as a basis for measuring growth. Psychological Bulletin, 108, 128-134.
18. Collins, L.M., Cliff, N., & Dent, C.W. (1988). The longitudinal Guttman simplex: A new methodology for measurement of dynamic constructs in longitudinal panel studies. Applied Psychological Measurement, 12, 217-230.
19. Collins, L.M., & Wugalter, S.E. (1992). Latent class models for stage-sequential dynamic latent variables. Multivariate Behavioral Research, 27, 131-157.
20. Craighead, W.E., Curry, J.F., & Ilardi, S.S. (1995). Relationship of Children's Depression Inventory factors to major depression among adolescents. Psychological Assessment, 7, 171-176.
21. Cudeck, R. (1989). Analysis of correlation matrices using covariance structure models. Psychological Bulletin, 105, 317-327.
22. Cunningham, W.R. (1980). Age comparative factor analysis of ability variables in adulthood and old age. Intelligence, 4, 133-149.
23. Curran, P.J., Bollen, K.A., Chen, F., Paxton, P., & Kirby, J.B. (2003). Finite sampling properties of the point estimates and confidence intervals of the RMSEA. Sociological Methods and Research, 32, 208-252.
24. Deary, I.J., Egan, V., Gibson, G.J., Austin, E.J., Brand, C.R., & Kellaghan, T. (1996). Intelligence and the differentiation hypothesis. Intelligence, 23, 105-132.
25. Efron, B., & Tibshirani, R.J. (1993). An introduction to the bootstrap. Boca Raton, FL: Chapman & Hall/ CRC.
26. Emmerich, W. (1968). Personality development and concepts of structure. Child Development, 39, 671-690. Garrett, H.E. (1938). Differentiable mental traits. The Psychological Record, 2, 259-298.
27. Garrett, H.E. (1946). A developmental theory of intelligence. American Psychologist, 1, 372-378.
28. Ghisletta, P., & Lindenberger, U. (2003). Age-based structural dynamics between perceptual speed and knowledge in the Berlin Aging Study: Direct evidence for ability dedifferentiation in old age. Psychology and Aging, 18, 696-713.
29. Hamaker, E.L., Dolan, C.V., & Molenaar, P.C.M. (2005). Statistical modeling of the individual: Rationale and application of multivariate stationary time series analysis. Multivariate Behavioral Research, 40, 207-233.
30. Hertzog, C., & Schaie, K.W. (1986). Stability and change in adult intelligence: 1. Analysis of longitudinal covariance structures. Psychology and Aging, 1, 159-171.
31. Hodges, K., & Craighead, W.E. (1990). Relationship of the Children's Depression Inventory factors to diagnosed depression. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 2, 489-492.
32. Holtzman, W.H. (1962). Methodological issues in P-technique. Psychological Bulletin, 59, 248-256.
33. Jones, C.J., & Nesselroade, J.R. (1990). Multivariate, replicated, single-subject, repeated measures designs and P-technique factor analysis: A review of intraindividual change studies. Experimental Aging Research, 16, 171-183.
34. Kaplan, D. (2008). An overview of Markov chain methods for the study of stage-sequential developmental processes. Developmental Psychology, 44, 457-467.
35. Langeheine, R., Stern, E., & van de Pol, F. (1994). State mastery learning: Dynamic models for longitudinal data. Applied Psychological Measurement, 18, 277-291.
36. Larsen, R.J., & Kasimatis, M. (1991). Day-to-day physical symptoms: Individual differences in the occurrence, duration, and emotional concomitants of minor daily illnesses. Journal of Personality, 59, 387-423.
37. Luborsky, L., & Mintz, J. (1972). The contribution of P-technique to personality, psychotherapy, and psychosomatic research. In R. M. Dreger (Ed.), Multivariate personality research: Contributions to the understanding of personality in honor of Raymond B. Cattell (pp. 387-410). Baton Rouge, LA: Claitor's.
38. MacCallum, R.C., Browne, M.W., & Sugawara, H.M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130-149.
39. McArdle, J.J. (1988). Dynamic but structural equation modeling of repeated measures data. In J. R. Nesselroade & R. B. Cattell (Eds.), The handbook of multivariate experimental psychology (Vol. 2, pp. 561-614). New York: Plenum.
40. McArdle, J.J., & Epstein, D. (1987). Latent growth curves within developmental structural equation models. Child Development, 58, 110-133.
41. Meredith, W., & Horn, J. (2001). The role of factorial invariance in modeling growth and change. In L. M. Collins & A. G. Sayer (Eds.), New methods for the analysis of change (pp. 203-240). Washington, DC: American Psychological Association.
42. Meredith, W., & Tisak, J. (1984, July). ''Tuckerizing'' curves. Paper presented at the annual meeting of the Psychometric Society, Santa Barbara, CA.
43. Meredith, W., & Tisak, J. (1990). Latent curve analysis. Psychometrika, 55, 107-122.
44. Molenaar, P.C.M. (2004). A manifesto on psychology as idiographic science: Bringing the person back into scientific psychology, this time forever. Measurement, 2, 201-218.
45. Molenaar, P.C.M., Gooijer, J.G.D., & Schmitz, B. (1992). Dynamic factor analysis of nonstationary multivariate time series. Psychometrika, 57, 333-349.
46. Nesselroade, J.R. (1983). Temporal selection and factor invariance in the study of development and change. In P. B. Baltes & J. O. G. Brim (Eds.), Life-span development and behaviour (Vol. 5, pp. 59-87). New York: Academic Press.
47. Nesselroade, J.R. (1991). Interindividual differences in intraindividual change. In L. M. Collins & J. L. Horn (Eds.), Best methods for the analysis of change: Recent advances, unanswered questions, future directions (pp. 92-105). Washington, DC: American Psychological Association.
48. Nesselroade, J.R., McArdle, J.J., Aggen, S.H., & Myers, J.M. (2002). Dynamic factor analysis models for representing process in multivariate time-series. In D. M. Moskowitz & S. L. Hershberger (Eds.), Modeling intraindividual variability with repeated measures data: Advances and techniques (pp. 235-265). Mahwah, NJ: Lawrence Erlbaum.
49. Nesselroade, J.R., & Ram, N. (2004). Studying intraindividual variability: What we have learned that will help us understand lives in context. Research in Human Development, 1, 9-29.
50. Ong, A.D., & Bergeman, C.S. (2004). The complexity of emotions in later life. Journal of Gerontology: Psychological Sciences, 59B, P117 - P122.
51. R Development Core Team. (2005). R: A language and environment for statistical computing. Vienna, Austria. (Version 2.2.1, ISBN 3-900051-07-0)
52. Rogosa, D., Brandt, D., & Zimowski, M. (1982). A growth curve approach to the measurement of change. Psychological Bulletin, 92, 726-748.
53. Rogosa, D., & Saner, H. (1995). Longitudinal data analysis examples with random coefficient models. Journal of Educational and Behavioral Statistics, 20, 149-170.
54. Rogosa, D., & Willett, J.B. (1985). Understanding correlates of change by modeling individual differences in growth. Psychometrika, 50, 203-228.
55. Spearman, C. (1927). The abilities of man: Their nature and measurement. New York: Macmillan.
56. Steiger, J.H., & Lind, J.C. (1980, May). Statistically-based tests for the number of common factors. Paper presented at the annual meeting of the Psychometric Society, Iowa City.
57. Vermunt, J.K., Langeheine, R., & Böckenholt, U. (1999). Discrete-time discrete-state latent Markov models with time-constant and time-varying covariates. Journal of Educational and Behavioral Statistics, 24, 179-207.
58. Werner, H. (1948). Comparative psychology of mental development (Rev. ed.). New York: International Universities Press.
59. Willett, J.B. (1988). Questions and answers in the measurement of change. In E. Z. Rothkopf (Ed.), Review of research in education (Vol. 15, pp. 345-422). Washington, DC: American Educational Research Association.