Modeling the co-development of correlated processes with longitudinal and cross-construct effects. | Zendy

Yaacov Petscher | Zendy; Jamie Quinn | Zendy; Richard K. Wagner | Zendy

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Modeling the co-development of correlated processes with longitudinal and cross-construct effects.

Author(s) -

Yaacov Petscher,

Jamie Quinn,

Richard K. Wagner

Publication year - 2016

Publication title -

developmental psychology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.318

H-Index - 213

eISSN - 1939-0599

pISSN - 0012-1649

DOI - 10.1037/dev0000172

Subject(s) - latent growth modeling , psychology , multilevel model , psycinfo , construct (python library) , developmental psychology , structural equation modeling , latent variable , growth curve (statistics) , fluency , longitudinal data , regression analysis , latent variable model , linear model , random effects model , reading (process) , cognitive psychology , econometrics , statistics , meta analysis , computer science , mathematics , medicine , law , data mining , programming language , mathematics education , medline , political science

Conceptualizations of developmental trends are driven by the particular method used to analyze the period of change of interest. Various techniques exist to analyze developmental data, including individual growth curve analysis in observed and latent frameworks, cross-lagged regression to assess interrelations among variables, and multilevel frameworks that consider time as nested within individual. In this paper, we report on findings from a latent change score analysis of oral reading fluency and reading comprehension data from a longitudinal sample of approximately 16,000 students from first to fourth grade. Results highlight the utility of latent change score models compared to alternative specifications of linear and nonlinear quadratic latent growth models as well as implications for modeling change with correlated traits. (PsycINFO Database Record

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