Psikhologicheskie Issledovaniya • ISSN 2075-7999
peer-reviewed • open access journal
      

 

Dodonova Y.A., Dodonov Y.S. On choosing a model for estimating individual differences in latent growth trajectories [Full text]

Full text in Russian: Додонова Ю.А., Додонов Ю.С. К вопросу о выборе модели при оценивании индивидуальных различий в траекториях латентного роста
Moscow State University of Psychology and Education, Moscow, Russia
Peoples’ Friendship University of Russia, Moscow, Russia

About authors
Suggested citation
Full text [PDF 391 KB]


Studies on the speed at which tasks of varying difficulties are processed frequently meet methodological obstacles, such as the difficulty to achieve reliable individual differences in parameters that describe response time growth with increasing task difficulty and the lack of stable correlations between growth parameters and external variables. In this computer simulation study, we demonstrate that instability and the systematic underestimation of correlations between growth parameters and external variables can be due to the choice of an inappropriate model to describe individual growth trajectories. Furthermore, the failure to choose a sufficiently flexible function for modeling can prevent the identification of individual differences in a shape of growth. Although we discuss our results and conclusions within the context of processing speed research, they are true for any studies that involve the modeling of latent change curves.

Keywords: latent growth modeling, computer simulation study, individual differences, speed of information processing, cognitive ability

 

Full text [PDF 391 KB] >>


References

Beauducel A., Brocke B. Intelligence and speed of information processing: further results and questions on Hick’s paradigm and beyond. Personality and Individual Differences, 1993, 15(6), 627–636. doi: 10.1016/0191-8869(93)90004-M

Blackwell R.J. Galileo, Bellarmine, and the Bible. Notre Dame: University of Notre Dame Press, 1991.

Dodonov Y.S., Dodonova Y.A. Response time analysis in cognitive tasks with increasing difficulty. Intelligence, 2012, 40(5), 379–394. doi: 10.1016/j.intell.2012.07.002

Duncan T.E., Duncan S.C. Modeling the processes of development via latent variable growth curve methodology. Structural Equation Modeling. 1995, 2(3), 187–213. doi: 10.1080/10705519509540009

Hick W.E. On the rate of gain of information. The Quarterly Journal of Experimental Psychology, 1952, 4(1), 11–26. doi: 10.1080/17470215208416600

Hunt E., MacLeod C.M. The sentence-verification paradigm: A case study of two conflicting aproaches to individual differences. Intelligence, 1978, 2(2), 129–144. doi: 10.1016/0160-2896(78)90004-1

Hyman R. Stimulus information as a determinant of reaction time. Journal of Experimental Psychology, 1953, 45(3), 188–196. doi: 10.1037/h0056940

Jensen A. Individual differences in the Hick paradigm. In: P.A. Vernon (Ed.), Speed of information processing and intelligence. Norwood, NJ: Ablex, 1987(а). pp. 101–175.

Jensen A.R. Process differences and individual differences in some cognitive tasks. Intelligence. 1987(b), 11(2), 107–136. doi: 10.1016/0160-2896(87)90001-8

Jensen A. The g factor. London: Praeger, 1998(а).

Jensen A. The suppressed relationship between IQ and the reaction time slope parameter of the Hick function. Intelligence, 1998(b), 26(1), 43–52. doi: 10.1016/S0160-2896(99)80051-8

Jensen A.R. Clocking the mind: Mental chronometry and individual differences. Amsterdam: Elsevier, 2006.

Jöreskog K.G., Sörbom D. LISREL VI: Analysis of linear structural relationship by maximum likelihood and least squares methods. Chicago: National Educational Resources, 1981.

Kornblum S. Sequential determinants of information processing in serial and discrete choice reaction time. Psychological Review, 1969, 76(2), 113–131. doi: 10.1037/h0027245

Lohman D.F. Component scores as residual variation (or why the intercept correlates best). Intelligence, 1994, 19(1), 1–11. doi: 10.1016/0160-2896(94)90048-5

McArdle J.J., Epstein D. Latent growth curves within developmental structural equation models. Child Development, 1987, 58(1), 110–133. doi: 10.2307/1130295

Meredith W., Tisak J. Latent curve analysis. Psychometrika, 1990, 55(1), 107–122. doi: 10.1007/BF02294746

Neubauer A.C. Intelligence and RT: A modified Hick paradigm and a new RT paradigm. Intelligence, 1991, 15(2), 175–193. doi: 10.1016/0160-2896(91)90029-D

Neubauer A.C., Riemann R., Mayer R., Angleitner A. Intelligence and reaction times in the Hick, Sternberg and Posner paradigms. Personality and Individual Differences, 1997, 22(6), 885–894. doi: 10.1016/S0191-8869(97)00003-2

Palmer J., MacLeod C.M, Hunt E., Davidson J.E. Information processing correlates of reading. Journal of Memory and Language, 1985, 24(1), 59–88. doi: 10.1016/0749-596X(85)90016-6

R Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. http://www.R-project.org/.

Rammsayer T.H., Brandler S. Performance on temporal information processing as an index of general intelligence. Intelligence, 2007, 35(2), 123–139. doi: 10.1016/j.intell.2006.04.007

Rosseel Y. lavaan: An R package for structural equation modeling. Journal of Statistical Software, 2012, 48(2), 1–36.

Roth E. Die Geschwinddigkeit der Verabeitung von Information und ihr Zusammenhang mit Intelligenz. Zeitschrift fuer Expermintelle und Angewandte Psychologie, 1964, 11(4), 616–622.

Schweizer K. The fixed-links model in combination with the polynomial function as a tool for investigating choice reaction time data. Structural Equation Modeling, 2006(a), 13(3), 403–419. doi: 10.1207/s15328007sem1303_4

Schweizer K. The fixed-links model for investigating the effects of general and specific processes on intelligence. Methodology, 2006(b), 2(4), 149–160. doi: 10.1027/1614-2241.2.4.149

Shannon C.E. A mathematical theory of communication. The Bell System Technical Journal, 1948, 27, 379–423, 623–656.

Sternberg S. High speed scanning in human memory. Science, 1966, 153(3736), 652–654. doi:10.1126/science.153.3736.652

Widaman K.F., Thompson J.S. On specifying the null model for incremental fit indices in structural equation modeling. Psychological Methods, 2003, 8(1), 16–37. doi: 10.1037/1082-989X.8.1.16

Received 24 September 2012. Date of publication: 22 February 2013.
Full text [PDF 391 KB] >>

About authors

Dodonova Yulia A. Ph.D., Research Associate, Moscow State University of Psychology and Education, Sretenka str., 29, 103051, Moscow, Russia; Peoples’ Friendship University of Russia, Miklukho-Maklaya, 6, 117198 Moscow, Russia.
E-mail: Этот адрес электронной почты защищен от спам-ботов. У вас должен быть включен JavaScript для просмотра.

Dodonov Yury S. Ph.D., Research Associate, Moscow State University of Psychology and Education, Sretenka str., 29, 103051 Moscow, Russia.
E-mail: Этот адрес электронной почты защищен от спам-ботов. У вас должен быть включен JavaScript для просмотра.

Suggested citation

Dodonova Y.A., Dodonov Y.S. On choosing a model for estimating individual differences in latent growth trajectories. Psikhologicheskie Issledovaniya, 2013, Vol. 6, No. 27, p. 3. http://psystudy.ru

Permanent URL: http://psystudy.ru/index.php/eng/2013v6n27e/825-dodonova27e.html

Full text [PDF 391 KB]
Back to top >>